<!-- This comment will put IE 6, 7 and 8 in quirks mode -->
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/>
<title>include/shark/Algorithms/QP/QpMcSimplexDecomp.h Source File</title>
<script type="text/javaScript" src="search/search.js"></script>
<script type="text/javascript" src="jquery.js"></script>
<script type="text/javascript" src="dynsections.js"></script>
<script src="https://polyfill.io/v3/polyfill.min.js?features=es6"></script>
<script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3.0.1/es5/tex-mml-chtml.js"></script>
<script src="../../mlstyle.js"></script>
<link href="../css/besser.css" rel="stylesheet" type="text/css"/>
</head>
<!-- pretty cool: each body gets an id tag which is the basename of the web page  -->
<!--              and allows for page-specific CSS. this is client-side scripted, -->
<!--              so the id will not yet show up in the served source code -->
<script type="text/javascript">
    jQuery(document).ready(function () {
        var url = jQuery(location).attr('href');
        var pname = url.substr(url.lastIndexOf("/")+1, url.lastIndexOf(".")-url.lastIndexOf("/")-1);
        jQuery('#this_url').html('<strong>' + pname + '</strong>');
        jQuery('body').attr('id', pname);
    });
</script>
<body>
    <div id="shark_old">
        <div id="wrap">
            <div id="header">
                <div id="site-name"><a href="../../sphinx_pages/build/html/index.html">Shark machine learning library</a></div>
                <ul id="nav">
                    <li >
                        <a href="../../sphinx_pages/build/html/rest_sources/installation.html">Installation</a>
                    </li>
		    <li >
                        <a href="../../sphinx_pages/build/html/rest_sources/tutorials/tutorials.html">Tutorials</a>
                    </li>
		    <li >
                        <a href="../../sphinx_pages/build/html/rest_sources/benchmark.html">Benchmarks</a>
                    </li>
                    <li class="active">
                        <a href="classes.html">Documentation</a>
                        <ul>
                            <li class="first"></li>
                            <li><a href="../../sphinx_pages/build/html/rest_sources/quickref/quickref.html">Quick references</a></li>
                            <li><a href="classes.html">Class list</a></li>
                            <li class="last"><a href="group__shark__globals.html">Global functions</a></li>
                        </ul>
                    </li>
                </ul>
            </div>
        </div>
    </div>
<div id="doxywrapper">
<!--
    <div id="global_doxytitle">Doxygen<br>Documentation:</div>
-->
    <div id="navrow_wrapper">
<!-- Generated by Doxygen 1.9.8 -->
<div id="nav-path" class="navpath">
  <ul>
<li class="navelem"><a class="el" href="dir_d44c64559bbebec7f509842c48db8b23.html">include</a></li><li class="navelem"><a class="el" href="dir_9d0c4981f10d03078bcfd5c74fe41ce8.html">shark</a></li><li class="navelem"><a class="el" href="dir_24fc231769ada4cfc8add7cd238ad0f8.html">Algorithms</a></li><li class="navelem"><a class="el" href="dir_92335953225e003073501ac6d6eaa70f.html">QP</a></li>  </ul>
</div>
</div><!-- top -->
<div class="header">
  <div class="headertitle"><div class="title">QpMcSimplexDecomp.h</div></div>
</div><!--header-->
<div class="contents">
<a href="_qp_mc_simplex_decomp_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">//===========================================================================</span><span class="comment"></span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="comment">/*!</span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="comment"> * </span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span><span class="comment"> *</span></div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment"> * \brief       Quadratic programming problem for multi-class SVMs</span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="comment"> * </span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span><span class="comment"> * </span></div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment"> * </span></div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="comment"> *</span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="comment"> * \author      T. Glasmachers</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span><span class="comment"> * \date        2007-2012</span></div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="comment"> *</span></div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="comment"> *</span></div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span><span class="comment"> * \par Copyright 1995-2017 Shark Development Team</span></div>
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno">   15</span><span class="comment"> * </span></div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span><span class="comment"> * &lt;BR&gt;&lt;HR&gt;</span></div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span><span class="comment"> * This file is part of Shark.</span></div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span><span class="comment"> * &lt;https://shark-ml.github.io/Shark/&gt;</span></div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span><span class="comment"> * </span></div>
<div class="line"><a id="l00020" name="l00020"></a><span class="lineno">   20</span><span class="comment"> * Shark is free software: you can redistribute it and/or modify</span></div>
<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span><span class="comment"> * it under the terms of the GNU Lesser General Public License as published </span></div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span><span class="comment"> * by the Free Software Foundation, either version 3 of the License, or</span></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span><span class="comment"> * (at your option) any later version.</span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span><span class="comment"> * </span></div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span><span class="comment"> * Shark is distributed in the hope that it will be useful,</span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span><span class="comment"> * but WITHOUT ANY WARRANTY; without even the implied warranty of</span></div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno">   27</span><span class="comment"> * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the</span></div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span><span class="comment"> * GNU Lesser General Public License for more details.</span></div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span><span class="comment"> * </span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno">   30</span><span class="comment"> * You should have received a copy of the GNU Lesser General Public License</span></div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span><span class="comment"> * along with Shark.  If not, see &lt;http://www.gnu.org/licenses/&gt;.</span></div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno">   32</span><span class="comment"> *</span></div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span><span class="comment"> */</span></div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span><span class="comment">//===========================================================================</span></div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span> </div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span> </div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno">   37</span><span class="preprocessor">#ifndef SHARK_ALGORITHMS_QP_QPMCSIMPLEXDECOMP_H</span></div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span><span class="preprocessor">#define SHARK_ALGORITHMS_QP_QPMCSIMPLEXDECOMP_H</span></div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span> </div>
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno">   40</span><span class="preprocessor">#include &lt;<a class="code" href="_qp_solver_8h.html">shark/Algorithms/QP/QpSolver.h</a>&gt;</span></div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span><span class="preprocessor">#include &lt;<a class="code" href="_qp_sparse_array_8h.html">shark/Algorithms/QP/QpSparseArray.h</a>&gt;</span></div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno">   42</span><span class="preprocessor">#include &lt;shark/Algorithms/QP/Impl/AnalyticProblems.h&gt;</span></div>
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno">   43</span><span class="preprocessor">#include &lt;<a class="code" href="_timer_8h.html">shark/Core/Timer.h</a>&gt;</span></div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span><span class="preprocessor">#include &lt;<a class="code" href="_dataset_8h.html">shark/Data/Dataset.h</a>&gt;</span></div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span> </div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span> </div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno">   47</span><span class="keyword">namespace </span><a class="code hl_namespace" href="namespaceshark.html" title="AbstractMultiObjectiveOptimizer.">shark</a> {</div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno">   48</span> </div>
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno">   49</span><span class="keyword">template</span> &lt;<span class="keyword">class</span> Matrix&gt;</div>
<div class="foldopen" id="foldopen00050" data-start="{" data-end="};">
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html">   50</a></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_qp_mc_simplex_decomp.html">QpMcSimplexDecomp</a></div>
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno">   51</span>{</div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno">   52</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#ac2dfe25a10f0c19a059d4a5625a19937">   53</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> Matrix::QpFloatType <a class="code hl_typedef" href="classshark_1_1_qp_mc_simplex_decomp.html#ac2dfe25a10f0c19a059d4a5625a19937">QpFloatType</a>;<span class="comment"></span></div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno">   54</span><span class="comment">    /// \brief Working set selection eturning th S2DO working set</span></div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno">   55</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno">   56</span><span class="comment">    /// This selection operator picks the first variable by maximum gradient, </span></div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno">   57</span><span class="comment">    /// the second by maximum unconstrained gain.</span></div>
<div class="foldopen" id="foldopen00058" data-start="{" data-end="};">
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_prefered_selection_strategy.html">   58</a></span><span class="comment"></span>    <span class="keyword">struct </span><a class="code hl_struct" href="structshark_1_1_qp_mc_simplex_decomp_1_1_prefered_selection_strategy.html" title="Working set selection eturning th S2DO working set.">PreferedSelectionStrategy</a>{</div>
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno">   59</span>        <span class="keyword">template</span>&lt;<span class="keyword">class</span> Problem&gt;</div>
<div class="foldopen" id="foldopen00060" data-start="{" data-end="}">
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_prefered_selection_strategy.html#aac71b28946c4fac90b4289227964365f">   60</a></span>        <span class="keywordtype">double</span> <a class="code hl_function" href="structshark_1_1_qp_mc_simplex_decomp_1_1_prefered_selection_strategy.html#aac71b28946c4fac90b4289227964365f">operator()</a>(Problem&amp; problem, std::size_t&amp; i, std::size_t&amp; j){</div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span>            <span class="comment">//todo move implementation here</span></div>
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno">   62</span>            <span class="keywordflow">return</span> problem.selectWorkingSet(i,j);</div>
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno">   63</span>        }</div>
</div>
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno">   64</span> </div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_prefered_selection_strategy.html#af129df59061923a301d6b6a15e985504">   65</a></span>        <span class="keywordtype">void</span> <a class="code hl_function" href="structshark_1_1_qp_mc_simplex_decomp_1_1_prefered_selection_strategy.html#af129df59061923a301d6b6a15e985504">reset</a>(){}</div>
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno">   66</span>    };</div>
</div>
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno">   67</span><span class="comment"></span> </div>
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno">   68</span><span class="comment">    /// Constructor</span></div>
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno">   69</span><span class="comment">    /// \param  kernel               kernel matrix - cache or pre-computed matrix</span></div>
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno">   70</span><span class="comment">    /// \param  M                   kernel modifiers in the format \f$ M_(y_i, p, y_j, q) = _M(classes*(y_i*|P|+p_i)+y_j, q) \f$</span></div>
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno">   71</span><span class="comment">    /// \param  target the target labels for the variables</span></div>
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno">   72</span><span class="comment">    /// \param linearMat the linear part of the problem</span></div>
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno">   73</span><span class="comment">    /// \param C upper bound for all box variables, lower bound is 0.</span></div>
<div class="foldopen" id="foldopen00074" data-start="{" data-end="}">
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a902ef2e3553bb5cf42a5126199301abe">   74</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a902ef2e3553bb5cf42a5126199301abe">QpMcSimplexDecomp</a>(</div>
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno">   75</span>        Matrix&amp; kernel,</div>
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno">   76</span>        <a class="code hl_class" href="classshark_1_1_qp_sparse_array.html" title="specialized container class for multi-class SVM problems">QpSparseArray&lt;QpFloatType&gt;</a> <span class="keyword">const</span>&amp; M,</div>
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno">   77</span>        <a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;unsigned int&gt;</a> <span class="keyword">const</span>&amp; target,</div>
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno">   78</span>        RealMatrix <span class="keyword">const</span>&amp; linearMat,</div>
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno">   79</span>        <span class="keywordtype">double</span> C</div>
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno">   80</span>    )</div>
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno">   81</span>    : <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ac8b9a895906060a9d50e13b0523d4255" title="kernel matrix (precomputed matrix or matrix cache)">m_kernelMatrix</a>(kernel)</div>
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno">   82</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a7b64dccd47c7db2a9fa4110b55b52c7c" title="kernel modifiers">m_M</a>(M)</div>
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno">   83</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>(C)</div>
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno">   84</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4b3c753187efbb58b433a76face7a52d" title="number of classes in the problem">m_classes</a>(<a class="code hl_function" href="group__shark__globals.html#ga1fee3b5830ae11a78109e8c0265c6569" title="Return the number of classes of a set of class labels with unsigned int label encoding.">numberOfClasses</a>(target))</div>
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno">   85</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>(linearMat.size2())</div>
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno">   86</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287" title="number of examples in the problem (size of the kernel matrix)">m_numExamples</a>(kernel.size())</div>
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno">   87</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a> * <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287" title="number of examples in the problem (size of the kernel matrix)">m_numExamples</a>)</div>
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno">   88</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#acae515e014c4002712b8d7204b2e5d36" title="linear part of the objective function">m_linear</a>(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>)</div>
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno">   89</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>,0.0)</div>
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno">   90</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>)</div>
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno">   91</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287" title="number of examples in the problem (size of the kernel matrix)">m_numExamples</a>)</div>
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno">   92</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>)</div>
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno">   93</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9b901d9fb12638fcbf12704c0bf41bcd" title="space for the example[i].var pointers">m_storage1</a>(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>)</div>
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno">   94</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a3e94df73fba2f12fcbdc923c062ff752" title="space for the example[i].avar pointers">m_storage2</a>(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>)</div>
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno">   95</span>    , <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af69f443110c3a0e0c6d34ec331c71a8a" title="should the m_problem use the shrinking heuristics?">m_useShrinking</a>(true){</div>
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno">   96</span>        <a class="code hl_define" href="_exception_8h.html#adce1f80097c69010f5eab2618fa2e971">SHARK_RUNTIME_CHECK</a>(target.<a class="code hl_function" href="group__shark__globals.html#ga814e8b0028cc90dd2af69805e8f8a04d" title="Returns the total number of elements.">numberOfElements</a>() == kernel.size(), <span class="stringliteral">&quot;size of kernel matrix and target vector do not agree&quot;</span>);</div>
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno">   97</span>        <a class="code hl_define" href="_exception_8h.html#adce1f80097c69010f5eab2618fa2e971">SHARK_RUNTIME_CHECK</a>(kernel.size() == linearMat.size1(), <span class="stringliteral">&quot;size of kernel matrix and linear factor to not agree&quot;</span>);</div>
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno">   98</span>        </div>
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno">   99</span>        <span class="comment">// prepare problem internal variables</span></div>
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno">  100</span>        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a> = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287" title="number of examples in the problem (size of the kernel matrix)">m_numExamples</a>;</div>
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno">  101</span>        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a> = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>;</div>
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno">  102</span>        <span class="keywordflow">for</span> (std::size_t v=0, i=0; i&lt;<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287" title="number of examples in the problem (size of the kernel matrix)">m_numExamples</a>; i++)</div>
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno">  103</span>        {</div>
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno">  104</span>            <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> y = target.<a class="code hl_function" href="group__shark__globals.html#ga0ea72a74a21d5ff59772516b83c4a58b">element</a>(i);</div>
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno">  105</span>            <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i].index = i;</div>
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno">  106</span>            <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i].y = y;</div>
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno">  107</span>            <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i].active = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>;</div>
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno">  108</span>            <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i].var = &amp;<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9b901d9fb12638fcbf12704c0bf41bcd" title="space for the example[i].var pointers">m_storage1</a>[<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a> * i];</div>
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno">  109</span>            <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i].avar = &amp;<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a3e94df73fba2f12fcbdc923c062ff752" title="space for the example[i].avar pointers">m_storage2</a>[<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a> * i];</div>
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno">  110</span>            <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i].varsum = 0;</div>
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno">  111</span>            <span class="keywordtype">double</span> k = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ac8b9a895906060a9d50e13b0523d4255" title="kernel matrix (precomputed matrix or matrix cache)">m_kernelMatrix</a>.entry(i, i);</div>
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno">  112</span>            <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i].diagonal = k;</div>
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno">  113</span>            <span class="keywordflow">for</span> (std::size_t p=0; p&lt;<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>; p++, v++)</div>
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno">  114</span>            {</div>
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno">  115</span>                <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].example = i;</div>
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno">  116</span>                <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].p = p;</div>
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno">  117</span>                <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].index = p;</div>
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno">  118</span>                <span class="keywordtype">double</span> Q = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a7b64dccd47c7db2a9fa4110b55b52c7c" title="kernel modifiers">m_M</a>(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4b3c753187efbb58b433a76face7a52d" title="number of classes in the problem">m_classes</a> * (y * <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a> + p) + y, p) * k;</div>
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno">  119</span>                <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].diagonal = Q;</div>
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno">  120</span>                <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9b901d9fb12638fcbf12704c0bf41bcd" title="space for the example[i].var pointers">m_storage1</a>[v] = v;</div>
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno">  121</span>                <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a3e94df73fba2f12fcbdc923c062ff752" title="space for the example[i].avar pointers">m_storage2</a>[v] = v;</div>
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno">  122</span>                </div>
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno">  123</span>                <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#acae515e014c4002712b8d7204b2e5d36" title="linear part of the objective function">m_linear</a>(v) = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(v) = linearMat(i,p);</div>
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno">  124</span>            }</div>
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno">  125</span>        }</div>
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno">  126</span>        <span class="comment">// initialize unshrinking to make valgrind happy.</span></div>
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno">  127</span>        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae4356261aaf70b6569308fa13f01a56a" title="true if the problem has already been unshrinked">bUnshrinked</a> = <span class="keyword">false</span>;</div>
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno">  128</span>    }</div>
</div>
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno">  129</span>    <span class="comment"></span></div>
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno">  130</span><span class="comment">    /// enable/disable shrinking</span></div>
<div class="foldopen" id="foldopen00131" data-start="{" data-end="}">
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#aca9c90b5417b11327ae5447322078986">  131</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#aca9c90b5417b11327ae5447322078986" title="enable/disable shrinking">setShrinking</a>(<span class="keywordtype">bool</span> shrinking = <span class="keyword">true</span>)</div>
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno">  132</span>    {</div>
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno">  133</span>        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af69f443110c3a0e0c6d34ec331c71a8a" title="should the m_problem use the shrinking heuristics?">m_useShrinking</a> = shrinking; </div>
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno">  134</span>    }</div>
</div>
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno">  135</span>    <span class="comment"></span></div>
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno">  136</span><span class="comment">    /// \brief Returns the solution found.</span></div>
<div class="foldopen" id="foldopen00137" data-start="{" data-end="}">
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#aa9b4ddd02acf37a4ba2f5183e5436b79">  137</a></span><span class="comment"></span>    RealMatrix <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#aa9b4ddd02acf37a4ba2f5183e5436b79" title="Returns the solution found.">solution</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno">  138</span>        RealMatrix solutionMatrix(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>,<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>,0);</div>
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno">  139</span>        <span class="keywordflow">for</span> (std::size_t v=0; v&lt;<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>; v++)</div>
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno">  140</span>        {</div>
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno">  141</span>            solutionMatrix(<a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a35458b4d12a371cf221c1643e7295072" title="Returns the original index of the example of a variable in the dataset before optimization.">originalIndex</a>(v),<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].p) = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v);</div>
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno">  142</span>        }</div>
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno">  143</span>        <span class="keywordflow">return</span> solutionMatrix;</div>
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno">  144</span>    }<span class="comment"></span></div>
</div>
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno">  145</span><span class="comment">    /// \brief Returns the gradient of the solution.</span></div>
<div class="foldopen" id="foldopen00146" data-start="{" data-end="}">
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a865bba06e22ecaf94d95e3284e28c184">  146</a></span><span class="comment"></span>    RealMatrix <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a865bba06e22ecaf94d95e3284e28c184" title="Returns the gradient of the solution.">solutionGradient</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno">  147</span>        RealMatrix solutionGradientMatrix(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>,<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>,0);</div>
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno">  148</span>        <span class="keywordflow">for</span> (std::size_t v=0; v&lt;<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>; v++)</div>
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno">  149</span>        {</div>
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno">  150</span>            solutionGradientMatrix(<a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a35458b4d12a371cf221c1643e7295072" title="Returns the original index of the example of a variable in the dataset before optimization.">originalIndex</a>(v),<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].p) = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(v);</div>
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno">  151</span>        }</div>
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno">  152</span>        <span class="keywordflow">return</span> solutionGradientMatrix;</div>
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno">  153</span>    }</div>
</div>
<div class="line"><a id="l00154" name="l00154"></a><span class="lineno">  154</span>    <span class="comment"></span></div>
<div class="line"><a id="l00155" name="l00155"></a><span class="lineno">  155</span><span class="comment">    /// \brief Compute the objective value of the current solution.</span></div>
<div class="foldopen" id="foldopen00156" data-start="{" data-end="}">
<div class="line"><a id="l00156" name="l00156"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#ab697e161708891d6a088a5f8ea14aabd">  156</a></span><span class="comment"></span>    <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#ab697e161708891d6a088a5f8ea14aabd" title="Compute the objective value of the current solution.">functionValue</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00157" name="l00157"></a><span class="lineno">  157</span>        <span class="keywordflow">return</span> 0.5*inner_prod(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>+<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#acae515e014c4002712b8d7204b2e5d36" title="linear part of the objective function">m_linear</a>,<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>);</div>
<div class="line"><a id="l00158" name="l00158"></a><span class="lineno">  158</span>    }</div>
</div>
<div class="line"><a id="l00159" name="l00159"></a><span class="lineno">  159</span>    </div>
<div class="foldopen" id="foldopen00160" data-start="{" data-end="}">
<div class="line"><a id="l00160" name="l00160"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a8cc961f63f6f3cb17ebda1b48e4ca3bc">  160</a></span>    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a8cc961f63f6f3cb17ebda1b48e4ca3bc">label</a>(std::size_t i){</div>
<div class="line"><a id="l00161" name="l00161"></a><span class="lineno">  161</span>        <span class="keywordflow">return</span> <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i].y;</div>
<div class="line"><a id="l00162" name="l00162"></a><span class="lineno">  162</span>    }</div>
</div>
<div class="line"><a id="l00163" name="l00163"></a><span class="lineno">  163</span>    </div>
<div class="foldopen" id="foldopen00164" data-start="{" data-end="}">
<div class="line"><a id="l00164" name="l00164"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a7ce0f79ca192b9cff806f6dd74180911">  164</a></span>    std::size_t <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a7ce0f79ca192b9cff806f6dd74180911">dimensions</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00165" name="l00165"></a><span class="lineno">  165</span>        <span class="keywordflow">return</span> <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>;</div>
<div class="line"><a id="l00166" name="l00166"></a><span class="lineno">  166</span>    }</div>
</div>
<div class="foldopen" id="foldopen00167" data-start="{" data-end="}">
<div class="line"><a id="l00167" name="l00167"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a7d1d145388dafe52b13d4537c185df9c">  167</a></span>    std::size_t <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a7d1d145388dafe52b13d4537c185df9c">cardP</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00168" name="l00168"></a><span class="lineno">  168</span>        <span class="keywordflow">return</span> <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>;</div>
<div class="line"><a id="l00169" name="l00169"></a><span class="lineno">  169</span>    }</div>
</div>
<div class="line"><a id="l00170" name="l00170"></a><span class="lineno">  170</span>    </div>
<div class="foldopen" id="foldopen00171" data-start="{" data-end="}">
<div class="line"><a id="l00171" name="l00171"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a2a6a69df2e864c4437c99c4b99718f69">  171</a></span>    std::size_t <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a2a6a69df2e864c4437c99c4b99718f69">getNumExamples</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00172" name="l00172"></a><span class="lineno">  172</span>        <span class="keywordflow">return</span> <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287" title="number of examples in the problem (size of the kernel matrix)">m_numExamples</a>;</div>
<div class="line"><a id="l00173" name="l00173"></a><span class="lineno">  173</span>    }</div>
</div>
<div class="line"><a id="l00174" name="l00174"></a><span class="lineno">  174</span>    <span class="comment"></span></div>
<div class="line"><a id="l00175" name="l00175"></a><span class="lineno">  175</span><span class="comment">    /// \brief change the linear part of the problem by some delta</span></div>
<div class="foldopen" id="foldopen00176" data-start="{" data-end="}">
<div class="line"><a id="l00176" name="l00176"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a4ec3b3bf8b8dc4d6861ac2f8756575d8">  176</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a4ec3b3bf8b8dc4d6861ac2f8756575d8" title="change the linear part of the problem by some delta">addDeltaLinear</a>(RealMatrix <span class="keyword">const</span>&amp; deltaLinear){</div>
<div class="line"><a id="l00177" name="l00177"></a><span class="lineno">  177</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(deltaLinear.size1() == <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287" title="number of examples in the problem (size of the kernel matrix)">m_numExamples</a>);</div>
<div class="line"><a id="l00178" name="l00178"></a><span class="lineno">  178</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(deltaLinear.size2() == <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>);</div>
<div class="line"><a id="l00179" name="l00179"></a><span class="lineno">  179</span>        <span class="keywordflow">for</span> (std::size_t v=0; v&lt;<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>; v++)</div>
<div class="line"><a id="l00180" name="l00180"></a><span class="lineno">  180</span>        {</div>
<div class="line"><a id="l00181" name="l00181"></a><span class="lineno">  181</span>            std::size_t p = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].p;</div>
<div class="line"><a id="l00182" name="l00182"></a><span class="lineno">  182</span>            <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(v) += deltaLinear(<a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a35458b4d12a371cf221c1643e7295072" title="Returns the original index of the example of a variable in the dataset before optimization.">originalIndex</a>(v),p); </div>
<div class="line"><a id="l00183" name="l00183"></a><span class="lineno">  183</span>            <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#acae515e014c4002712b8d7204b2e5d36" title="linear part of the objective function">m_linear</a>(v) += deltaLinear(<a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a35458b4d12a371cf221c1643e7295072" title="Returns the original index of the example of a variable in the dataset before optimization.">originalIndex</a>(v),p);</div>
<div class="line"><a id="l00184" name="l00184"></a><span class="lineno">  184</span>        }</div>
<div class="line"><a id="l00185" name="l00185"></a><span class="lineno">  185</span>    }</div>
</div>
<div class="line"><a id="l00186" name="l00186"></a><span class="lineno">  186</span>    </div>
<div class="foldopen" id="foldopen00187" data-start="{" data-end="}">
<div class="line"><a id="l00187" name="l00187"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#ac8de8b9664c3e7d61c88a8060e3ed7ac">  187</a></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#ac8de8b9664c3e7d61c88a8060e3ed7ac">updateSMO</a>(std::size_t v, std::size_t w){</div>
<div class="line"><a id="l00188" name="l00188"></a><span class="lineno">  188</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(v &lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a>);</div>
<div class="line"><a id="l00189" name="l00189"></a><span class="lineno">  189</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(w &lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a>);</div>
<div class="line"><a id="l00190" name="l00190"></a><span class="lineno">  190</span>        <span class="comment">// update</span></div>
<div class="line"><a id="l00191" name="l00191"></a><span class="lineno">  191</span>        <span class="keywordflow">if</span> (v == w)</div>
<div class="line"><a id="l00192" name="l00192"></a><span class="lineno">  192</span>        {</div>
<div class="line"><a id="l00193" name="l00193"></a><span class="lineno">  193</span>            <span class="comment">// Limit case of a single variable;</span></div>
<div class="line"><a id="l00194" name="l00194"></a><span class="lineno">  194</span>            std::size_t i = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].example;</div>
<div class="line"><a id="l00195" name="l00195"></a><span class="lineno">  195</span>            <a class="code hl_define" href="_exception_8h.html#a73abb5049a0168d72a48e72dda41708b">SHARK_ASSERT</a>(i &lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>);</div>
<div class="line"><a id="l00196" name="l00196"></a><span class="lineno">  196</span>            std::size_t p = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].p;</div>
<div class="line"><a id="l00197" name="l00197"></a><span class="lineno">  197</span>            <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> y = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i].y;</div>
<div class="line"><a id="l00198" name="l00198"></a><span class="lineno">  198</span>            std::size_t r = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a> * y + p;</div>
<div class="line"><a id="l00199" name="l00199"></a><span class="lineno">  199</span>            <span class="keywordtype">double</span>&amp; varsum = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i].varsum;</div>
<div class="line"><a id="l00200" name="l00200"></a><span class="lineno">  200</span>            <span class="comment">//the upper bound depends on the values of the variables of the other classes.</span></div>
<div class="line"><a id="l00201" name="l00201"></a><span class="lineno">  201</span>            <span class="keywordtype">double</span> upperBound = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>-varsum+<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v);</div>
<div class="line"><a id="l00202" name="l00202"></a><span class="lineno">  202</span>            </div>
<div class="line"><a id="l00203" name="l00203"></a><span class="lineno">  203</span>            <a class="code hl_typedef" href="classshark_1_1_qp_mc_simplex_decomp.html#ac2dfe25a10f0c19a059d4a5625a19937">QpFloatType</a>* q = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ac8b9a895906060a9d50e13b0523d4255" title="kernel matrix (precomputed matrix or matrix cache)">m_kernelMatrix</a>.row(i, 0, <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>);</div>
<div class="line"><a id="l00204" name="l00204"></a><span class="lineno">  204</span>            <span class="keywordtype">double</span> Qvv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].diagonal;</div>
<div class="line"><a id="l00205" name="l00205"></a><span class="lineno">  205</span>            <span class="keywordtype">double</span> mu = -<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v);</div>
<div class="line"><a id="l00206" name="l00206"></a><span class="lineno">  206</span>            detail::solveQuadraticEdge(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v),<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(v),Qvv,0,upperBound);</div>
<div class="line"><a id="l00207" name="l00207"></a><span class="lineno">  207</span>            mu += <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v);</div>
<div class="line"><a id="l00208" name="l00208"></a><span class="lineno">  208</span>            <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a23aa81fc5a1341bacbbb65f4bba9bd38">updateVarsum</a>(i,mu);</div>
<div class="line"><a id="l00209" name="l00209"></a><span class="lineno">  209</span>            <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a2407864545443c298157fb489c3038f3">gradientUpdate</a>(r, mu, q);</div>
<div class="line"><a id="l00210" name="l00210"></a><span class="lineno">  210</span>        }</div>
<div class="line"><a id="l00211" name="l00211"></a><span class="lineno">  211</span>        <span class="keywordflow">else</span></div>
<div class="line"><a id="l00212" name="l00212"></a><span class="lineno">  212</span>        {</div>
<div class="line"><a id="l00213" name="l00213"></a><span class="lineno">  213</span>            <span class="comment">// S2DO</span></div>
<div class="line"><a id="l00214" name="l00214"></a><span class="lineno">  214</span>            std::size_t iv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].example;</div>
<div class="line"><a id="l00215" name="l00215"></a><span class="lineno">  215</span>            <a class="code hl_define" href="_exception_8h.html#a73abb5049a0168d72a48e72dda41708b">SHARK_ASSERT</a>(iv &lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>);</div>
<div class="line"><a id="l00216" name="l00216"></a><span class="lineno">  216</span>            std::size_t pv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].p;</div>
<div class="line"><a id="l00217" name="l00217"></a><span class="lineno">  217</span>            <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[iv].y;</div>
<div class="line"><a id="l00218" name="l00218"></a><span class="lineno">  218</span>            <span class="keywordtype">double</span>&amp; varsumv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[iv].varsum;</div>
<div class="line"><a id="l00219" name="l00219"></a><span class="lineno">  219</span> </div>
<div class="line"><a id="l00220" name="l00220"></a><span class="lineno">  220</span>            std::size_t iw = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[w].example;</div>
<div class="line"><a id="l00221" name="l00221"></a><span class="lineno">  221</span>            <a class="code hl_define" href="_exception_8h.html#a73abb5049a0168d72a48e72dda41708b">SHARK_ASSERT</a>(iw &lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>);</div>
<div class="line"><a id="l00222" name="l00222"></a><span class="lineno">  222</span>            std::size_t pw = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[w].p;</div>
<div class="line"><a id="l00223" name="l00223"></a><span class="lineno">  223</span>            <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yw = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[iw].y;</div>
<div class="line"><a id="l00224" name="l00224"></a><span class="lineno">  224</span>            <span class="keywordtype">double</span>&amp; varsumw = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[iw].varsum;</div>
<div class="line"><a id="l00225" name="l00225"></a><span class="lineno">  225</span> </div>
<div class="line"><a id="l00226" name="l00226"></a><span class="lineno">  226</span>            <span class="comment">// get the matrix rows corresponding to the working set</span></div>
<div class="line"><a id="l00227" name="l00227"></a><span class="lineno">  227</span>            <a class="code hl_typedef" href="classshark_1_1_qp_mc_simplex_decomp.html#ac2dfe25a10f0c19a059d4a5625a19937">QpFloatType</a>* qv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ac8b9a895906060a9d50e13b0523d4255" title="kernel matrix (precomputed matrix or matrix cache)">m_kernelMatrix</a>.row(iv, 0, <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>);</div>
<div class="line"><a id="l00228" name="l00228"></a><span class="lineno">  228</span>            <a class="code hl_typedef" href="classshark_1_1_qp_mc_simplex_decomp.html#ac2dfe25a10f0c19a059d4a5625a19937">QpFloatType</a>* qw = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ac8b9a895906060a9d50e13b0523d4255" title="kernel matrix (precomputed matrix or matrix cache)">m_kernelMatrix</a>.row(iw, 0, <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>);</div>
<div class="line"><a id="l00229" name="l00229"></a><span class="lineno">  229</span>            std::size_t rv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>*yv+pv;</div>
<div class="line"><a id="l00230" name="l00230"></a><span class="lineno">  230</span>            std::size_t rw = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>*yw+pw;</div>
<div class="line"><a id="l00231" name="l00231"></a><span class="lineno">  231</span> </div>
<div class="line"><a id="l00232" name="l00232"></a><span class="lineno">  232</span>            <span class="comment">// get the Q-matrix restricted to the working set</span></div>
<div class="line"><a id="l00233" name="l00233"></a><span class="lineno">  233</span>            <span class="keywordtype">double</span> Qvv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].diagonal;</div>
<div class="line"><a id="l00234" name="l00234"></a><span class="lineno">  234</span>            <span class="keywordtype">double</span> Qww = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[w].diagonal;</div>
<div class="line"><a id="l00235" name="l00235"></a><span class="lineno">  235</span>            <span class="keywordtype">double</span> Qvw = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a7b64dccd47c7db2a9fa4110b55b52c7c" title="kernel modifiers">m_M</a>(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4b3c753187efbb58b433a76face7a52d" title="number of classes in the problem">m_classes</a> * rv + yw, pw) * qv[iw];</div>
<div class="line"><a id="l00236" name="l00236"></a><span class="lineno">  236</span>            </div>
<div class="line"><a id="l00237" name="l00237"></a><span class="lineno">  237</span>            <span class="comment">//same sample - simplex case</span></div>
<div class="line"><a id="l00238" name="l00238"></a><span class="lineno">  238</span>            <span class="keywordtype">double</span> mu_v = -<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v);</div>
<div class="line"><a id="l00239" name="l00239"></a><span class="lineno">  239</span>            <span class="keywordtype">double</span> mu_w = -<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(w);</div>
<div class="line"><a id="l00240" name="l00240"></a><span class="lineno">  240</span>            <span class="keywordflow">if</span>(iv == iw){</div>
<div class="line"><a id="l00241" name="l00241"></a><span class="lineno">  241</span>                </div>
<div class="line"><a id="l00242" name="l00242"></a><span class="lineno">  242</span>                <span class="keywordtype">double</span> upperBound = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>-varsumv+<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v)+<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(w);</div>
<div class="line"><a id="l00243" name="l00243"></a><span class="lineno">  243</span>                <span class="comment">// solve the sub-problem and update the gradient using the step sizes mu</span></div>
<div class="line"><a id="l00244" name="l00244"></a><span class="lineno">  244</span>                detail::solveQuadratic2DTriangle(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v), <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(w),</div>
<div class="line"><a id="l00245" name="l00245"></a><span class="lineno">  245</span>                    <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(v), <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(w),</div>
<div class="line"><a id="l00246" name="l00246"></a><span class="lineno">  246</span>                    Qvv, Qvw, Qww,</div>
<div class="line"><a id="l00247" name="l00247"></a><span class="lineno">  247</span>                    upperBound</div>
<div class="line"><a id="l00248" name="l00248"></a><span class="lineno">  248</span>                );</div>
<div class="line"><a id="l00249" name="l00249"></a><span class="lineno">  249</span>                mu_v += <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v);</div>
<div class="line"><a id="l00250" name="l00250"></a><span class="lineno">  250</span>                mu_w += <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(w);</div>
<div class="line"><a id="l00251" name="l00251"></a><span class="lineno">  251</span>                <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a23aa81fc5a1341bacbbb65f4bba9bd38">updateVarsum</a>(iv,mu_v+mu_w);</div>
<div class="line"><a id="l00252" name="l00252"></a><span class="lineno">  252</span>            }</div>
<div class="line"><a id="l00253" name="l00253"></a><span class="lineno">  253</span>            <span class="keywordflow">else</span>{</div>
<div class="line"><a id="l00254" name="l00254"></a><span class="lineno">  254</span>                <span class="keywordtype">double</span> Uv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>-varsumv+<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v);</div>
<div class="line"><a id="l00255" name="l00255"></a><span class="lineno">  255</span>                <span class="keywordtype">double</span> Uw = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>-varsumw+<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(w);</div>
<div class="line"><a id="l00256" name="l00256"></a><span class="lineno">  256</span>                <span class="comment">// solve the sub-problem and update the gradient using the step sizes mu</span></div>
<div class="line"><a id="l00257" name="l00257"></a><span class="lineno">  257</span>                detail::solveQuadratic2DBox(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v), <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(w),</div>
<div class="line"><a id="l00258" name="l00258"></a><span class="lineno">  258</span>                    <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(v), <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(w),</div>
<div class="line"><a id="l00259" name="l00259"></a><span class="lineno">  259</span>                    Qvv, Qvw, Qww,</div>
<div class="line"><a id="l00260" name="l00260"></a><span class="lineno">  260</span>                    0, Uv, 0, Uw</div>
<div class="line"><a id="l00261" name="l00261"></a><span class="lineno">  261</span>                );</div>
<div class="line"><a id="l00262" name="l00262"></a><span class="lineno">  262</span>                mu_v += <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v);</div>
<div class="line"><a id="l00263" name="l00263"></a><span class="lineno">  263</span>                mu_w += <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(w);</div>
<div class="line"><a id="l00264" name="l00264"></a><span class="lineno">  264</span>                <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a23aa81fc5a1341bacbbb65f4bba9bd38">updateVarsum</a>(iv,mu_v);</div>
<div class="line"><a id="l00265" name="l00265"></a><span class="lineno">  265</span>                <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a23aa81fc5a1341bacbbb65f4bba9bd38">updateVarsum</a>(iw,mu_w);</div>
<div class="line"><a id="l00266" name="l00266"></a><span class="lineno">  266</span>            }</div>
<div class="line"><a id="l00267" name="l00267"></a><span class="lineno">  267</span>            </div>
<div class="line"><a id="l00268" name="l00268"></a><span class="lineno">  268</span>            <span class="keywordtype">double</span> varsumvo = 0;</div>
<div class="line"><a id="l00269" name="l00269"></a><span class="lineno">  269</span>            <span class="keywordflow">for</span>(std::size_t p = 0; p != <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>; ++p){</div>
<div class="line"><a id="l00270" name="l00270"></a><span class="lineno">  270</span>                std::size_t varIndex = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[iv].var[p];</div>
<div class="line"><a id="l00271" name="l00271"></a><span class="lineno">  271</span>                varsumvo += <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>[varIndex];</div>
<div class="line"><a id="l00272" name="l00272"></a><span class="lineno">  272</span>            }</div>
<div class="line"><a id="l00273" name="l00273"></a><span class="lineno">  273</span>            <span class="keywordtype">double</span> varsumwo = 0;</div>
<div class="line"><a id="l00274" name="l00274"></a><span class="lineno">  274</span>            <span class="keywordflow">for</span>(std::size_t p = 0; p != <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>; ++p){</div>
<div class="line"><a id="l00275" name="l00275"></a><span class="lineno">  275</span>                std::size_t varIndex = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[iw].var[p];</div>
<div class="line"><a id="l00276" name="l00276"></a><span class="lineno">  276</span>                varsumwo += <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>[varIndex];</div>
<div class="line"><a id="l00277" name="l00277"></a><span class="lineno">  277</span>            }</div>
<div class="line"><a id="l00278" name="l00278"></a><span class="lineno">  278</span>            <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a2407864545443c298157fb489c3038f3">gradientUpdate</a>(rv, mu_v, qv);</div>
<div class="line"><a id="l00279" name="l00279"></a><span class="lineno">  279</span>            <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a2407864545443c298157fb489c3038f3">gradientUpdate</a>(rw, mu_w, qw);</div>
<div class="line"><a id="l00280" name="l00280"></a><span class="lineno">  280</span>        }</div>
<div class="line"><a id="l00281" name="l00281"></a><span class="lineno">  281</span>    }</div>
</div>
<div class="line"><a id="l00282" name="l00282"></a><span class="lineno">  282</span>    <span class="comment"></span></div>
<div class="line"><a id="l00283" name="l00283"></a><span class="lineno">  283</span><span class="comment">    /// Shrink the problem</span></div>
<div class="foldopen" id="foldopen00284" data-start="{" data-end="}">
<div class="line"><a id="l00284" name="l00284"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#aca9f261b3af439c641c5f198ab31edc1">  284</a></span><span class="comment"></span>    <span class="keywordtype">bool</span> <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#aca9f261b3af439c641c5f198ab31edc1" title="Shrink the problem.">shrink</a>(<span class="keywordtype">double</span> epsilon)</div>
<div class="line"><a id="l00285" name="l00285"></a><span class="lineno">  285</span>    {</div>
<div class="line"><a id="l00286" name="l00286"></a><span class="lineno">  286</span>        <span class="keywordflow">if</span>(! <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af69f443110c3a0e0c6d34ec331c71a8a" title="should the m_problem use the shrinking heuristics?">m_useShrinking</a>)</div>
<div class="line"><a id="l00287" name="l00287"></a><span class="lineno">  287</span>            <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a id="l00288" name="l00288"></a><span class="lineno">  288</span>        <span class="keywordflow">if</span> (! <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae4356261aaf70b6569308fa13f01a56a" title="true if the problem has already been unshrinked">bUnshrinked</a>)</div>
<div class="line"><a id="l00289" name="l00289"></a><span class="lineno">  289</span>        {</div>
<div class="line"><a id="l00290" name="l00290"></a><span class="lineno">  290</span>            <span class="keywordflow">if</span> (<a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a62b40d1335f1aa500d790cf6b5e0d735" title="return the largest KKT violation">checkKKT</a>() &lt; 10.0 * epsilon)</div>
<div class="line"><a id="l00291" name="l00291"></a><span class="lineno">  291</span>            {</div>
<div class="line"><a id="l00292" name="l00292"></a><span class="lineno">  292</span>                <span class="comment">// unshrink the problem at this accuracy level</span></div>
<div class="line"><a id="l00293" name="l00293"></a><span class="lineno">  293</span>                <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a5e41ddc4c2f813b5c50dd3e5df4f2697" title="Activate all m_numVariables.">unshrink</a>();</div>
<div class="line"><a id="l00294" name="l00294"></a><span class="lineno">  294</span>                <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae4356261aaf70b6569308fa13f01a56a" title="true if the problem has already been unshrinked">bUnshrinked</a> = <span class="keyword">true</span>;</div>
<div class="line"><a id="l00295" name="l00295"></a><span class="lineno">  295</span>            }</div>
<div class="line"><a id="l00296" name="l00296"></a><span class="lineno">  296</span>        }</div>
<div class="line"><a id="l00297" name="l00297"></a><span class="lineno">  297</span>        </div>
<div class="line"><a id="l00298" name="l00298"></a><span class="lineno">  298</span>        <span class="comment">//iterate through all simplices.</span></div>
<div class="line"><a id="l00299" name="l00299"></a><span class="lineno">  299</span>        <span class="keywordflow">for</span> (std::size_t i = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>; i &gt; 0; i--){</div>
<div class="line"><a id="l00300" name="l00300"></a><span class="lineno">  300</span>            <a class="code hl_struct" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html" title="data structure describing one training example">Example</a> <span class="keyword">const</span>&amp; ex = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i-1];</div>
<div class="line"><a id="l00301" name="l00301"></a><span class="lineno">  301</span>            std::pair&lt;std::pair&lt;double,std::size_t&gt;,std::pair&lt;double,std::size_t&gt; &gt; pair = <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#abed9aa58f4c24140ba445737987a6f98" title="For a given simplex returns the MVP indicies (max_up,min_down)">getSimplexMVP</a>(ex);</div>
<div class="line"><a id="l00302" name="l00302"></a><span class="lineno">  302</span>            <span class="keywordtype">double</span> up = pair.first.first;</div>
<div class="line"><a id="l00303" name="l00303"></a><span class="lineno">  303</span>            <span class="keywordtype">double</span> down = pair.second.first;</div>
<div class="line"><a id="l00304" name="l00304"></a><span class="lineno">  304</span>            </div>
<div class="line"><a id="l00305" name="l00305"></a><span class="lineno">  305</span>            <span class="comment">//check the simplex for possible search directions</span></div>
<div class="line"><a id="l00306" name="l00306"></a><span class="lineno">  306</span>            <span class="comment">//case 1:  simplex is bounded and stays at the bound, in this case proceed as in MVP</span></div>
<div class="line"><a id="l00307" name="l00307"></a><span class="lineno">  307</span>            <span class="keywordflow">if</span>(down &gt; 0 &amp;&amp; ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ac5aea03b47634b4edeaf71099548433c" title="total sum of all variables of this example">varsum</a> == <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a> &amp;&amp; up-down &gt; 0){</div>
<div class="line"><a id="l00308" name="l00308"></a><span class="lineno">  308</span>                <span class="keywordtype">int</span> pc = (int)ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aed59b679c1979d9f8ed433f5f56716ab" title="number of active variables">active</a>;</div>
<div class="line"><a id="l00309" name="l00309"></a><span class="lineno">  309</span>                <span class="keywordflow">for</span>(<span class="keywordtype">int</span> p = pc-1; p &gt;= 0; --p){</div>
<div class="line"><a id="l00310" name="l00310"></a><span class="lineno">  310</span>                    <span class="keywordtype">double</span> a = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[p]);</div>
<div class="line"><a id="l00311" name="l00311"></a><span class="lineno">  311</span>                    <span class="keywordtype">double</span> g = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[p]);</div>
<div class="line"><a id="l00312" name="l00312"></a><span class="lineno">  312</span>                    <span class="comment">//if we can&#39;t do a step along the simplex, we can shrink the variable.</span></div>
<div class="line"><a id="l00313" name="l00313"></a><span class="lineno">  313</span>                    <span class="keywordflow">if</span>(a == 0 &amp;&amp; g-down &lt; 0){</div>
<div class="line"><a id="l00314" name="l00314"></a><span class="lineno">  314</span>                        <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a1d59e69be46dee9ca569fe8f4a4116d3" title="shrink a variable">deactivateVariable</a>(ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[p]);</div>
<div class="line"><a id="l00315" name="l00315"></a><span class="lineno">  315</span>                    }</div>
<div class="line"><a id="l00316" name="l00316"></a><span class="lineno">  316</span>                    <span class="keywordflow">else</span> <span class="keywordflow">if</span> (a == <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a> &amp;&amp; up-g &lt; 0){</div>
<div class="line"><a id="l00317" name="l00317"></a><span class="lineno">  317</span>                        <span class="comment">//shrinking this variable means, that the whole simplex can&#39;t move,</span></div>
<div class="line"><a id="l00318" name="l00318"></a><span class="lineno">  318</span>                        <span class="comment">//so shrink every variable, even the ones that previously couldn&#39;t</span></div>
<div class="line"><a id="l00319" name="l00319"></a><span class="lineno">  319</span>                        <span class="comment">//be shrinked</span></div>
<div class="line"><a id="l00320" name="l00320"></a><span class="lineno">  320</span>                        <span class="keywordflow">for</span>(<span class="keywordtype">int</span> q = (<span class="keywordtype">int</span>)ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aed59b679c1979d9f8ed433f5f56716ab" title="number of active variables">active</a>; q &gt;= 0; --q){</div>
<div class="line"><a id="l00321" name="l00321"></a><span class="lineno">  321</span>                            <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a1d59e69be46dee9ca569fe8f4a4116d3" title="shrink a variable">deactivateVariable</a>(ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[q]);</div>
<div class="line"><a id="l00322" name="l00322"></a><span class="lineno">  322</span>                        }</div>
<div class="line"><a id="l00323" name="l00323"></a><span class="lineno">  323</span>                        p = 0;</div>
<div class="line"><a id="l00324" name="l00324"></a><span class="lineno">  324</span>                    }</div>
<div class="line"><a id="l00325" name="l00325"></a><span class="lineno">  325</span>                }</div>
<div class="line"><a id="l00326" name="l00326"></a><span class="lineno">  326</span>            }</div>
<div class="line"><a id="l00327" name="l00327"></a><span class="lineno">  327</span>            <span class="comment">//case 2: all variables are zero and pushed against the boundary</span></div>
<div class="line"><a id="l00328" name="l00328"></a><span class="lineno">  328</span>            <span class="comment">// -&gt; shrink the example</span></div>
<div class="line"><a id="l00329" name="l00329"></a><span class="lineno">  329</span>            <span class="keywordflow">else</span> <span class="keywordflow">if</span>(ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ac5aea03b47634b4edeaf71099548433c" title="total sum of all variables of this example">varsum</a> == 0 &amp;&amp; up &lt; 0){</div>
<div class="line"><a id="l00330" name="l00330"></a><span class="lineno">  330</span>                <span class="keywordtype">int</span> pc = (int)ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aed59b679c1979d9f8ed433f5f56716ab" title="number of active variables">active</a>; </div>
<div class="line"><a id="l00331" name="l00331"></a><span class="lineno">  331</span>                <span class="keywordflow">for</span>(<span class="keywordtype">int</span> p = pc-1; p &gt;= 0; --p){</div>
<div class="line"><a id="l00332" name="l00332"></a><span class="lineno">  332</span>                    <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a1d59e69be46dee9ca569fe8f4a4116d3" title="shrink a variable">deactivateVariable</a>(ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[p]);</div>
<div class="line"><a id="l00333" name="l00333"></a><span class="lineno">  333</span>                }</div>
<div class="line"><a id="l00334" name="l00334"></a><span class="lineno">  334</span>            }</div>
<div class="line"><a id="l00335" name="l00335"></a><span class="lineno">  335</span>            <span class="comment">//case 3: the simplex is not bounded and there are free variables. </span></div>
<div class="line"><a id="l00336" name="l00336"></a><span class="lineno">  336</span>            <span class="comment">//in this case we currently do not shrink</span></div>
<div class="line"><a id="l00337" name="l00337"></a><span class="lineno">  337</span>            <span class="comment">//as a variable might get bounded at some point which means that all variables</span></div>
<div class="line"><a id="l00338" name="l00338"></a><span class="lineno">  338</span>            <span class="comment">//can be important again.</span></div>
<div class="line"><a id="l00339" name="l00339"></a><span class="lineno">  339</span>            <span class="comment">//else{</span></div>
<div class="line"><a id="l00340" name="l00340"></a><span class="lineno">  340</span>            <span class="comment">//}</span></div>
<div class="line"><a id="l00341" name="l00341"></a><span class="lineno">  341</span>            </div>
<div class="line"><a id="l00342" name="l00342"></a><span class="lineno">  342</span>        }</div>
<div class="line"><a id="l00343" name="l00343"></a><span class="lineno">  343</span><span class="comment">//      std::cout&lt;&lt;&quot;shrunk. remaining: &quot;&lt;&lt;m_activeEx&lt;&lt;&quot;,&quot;&lt;&lt;m_activeVar&lt;&lt;std::endl;</span></div>
<div class="line"><a id="l00344" name="l00344"></a><span class="lineno">  344</span>        <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a id="l00345" name="l00345"></a><span class="lineno">  345</span>    }</div>
</div>
<div class="line"><a id="l00346" name="l00346"></a><span class="lineno">  346</span><span class="comment"></span> </div>
<div class="line"><a id="l00347" name="l00347"></a><span class="lineno">  347</span><span class="comment">    /// Activate all m_numVariables</span></div>
<div class="foldopen" id="foldopen00348" data-start="{" data-end="}">
<div class="line"><a id="l00348" name="l00348"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a5e41ddc4c2f813b5c50dd3e5df4f2697">  348</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a5e41ddc4c2f813b5c50dd3e5df4f2697" title="Activate all m_numVariables.">unshrink</a>()</div>
<div class="line"><a id="l00349" name="l00349"></a><span class="lineno">  349</span>    {</div>
<div class="line"><a id="l00350" name="l00350"></a><span class="lineno">  350</span>        <span class="keywordflow">if</span> (<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a> == <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>) <span class="keywordflow">return</span>;</div>
<div class="line"><a id="l00351" name="l00351"></a><span class="lineno">  351</span> </div>
<div class="line"><a id="l00352" name="l00352"></a><span class="lineno">  352</span>        <span class="comment">// compute the inactive m_gradient components (quadratic time complexity)</span></div>
<div class="line"><a id="l00353" name="l00353"></a><span class="lineno">  353</span>        subrange(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>, <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a>, <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>) = subrange(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#acae515e014c4002712b8d7204b2e5d36" title="linear part of the objective function">m_linear</a>, <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a>, <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>);</div>
<div class="line"><a id="l00354" name="l00354"></a><span class="lineno">  354</span>        <span class="keywordflow">for</span> (std::size_t v = 0; v != <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>; v++)</div>
<div class="line"><a id="l00355" name="l00355"></a><span class="lineno">  355</span>        {</div>
<div class="line"><a id="l00356" name="l00356"></a><span class="lineno">  356</span>            <span class="keywordtype">double</span> mu = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v);</div>
<div class="line"><a id="l00357" name="l00357"></a><span class="lineno">  357</span>            <span class="keywordflow">if</span> (mu == 0.0) <span class="keywordflow">continue</span>;</div>
<div class="line"><a id="l00358" name="l00358"></a><span class="lineno">  358</span> </div>
<div class="line"><a id="l00359" name="l00359"></a><span class="lineno">  359</span>            std::size_t iv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].example;</div>
<div class="line"><a id="l00360" name="l00360"></a><span class="lineno">  360</span>            std::size_t pv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].p;</div>
<div class="line"><a id="l00361" name="l00361"></a><span class="lineno">  361</span>            <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[iv].y;</div>
<div class="line"><a id="l00362" name="l00362"></a><span class="lineno">  362</span>            std::size_t r = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a> * yv + pv;</div>
<div class="line"><a id="l00363" name="l00363"></a><span class="lineno">  363</span>            std::vector&lt;QpFloatType&gt; q(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287" title="number of examples in the problem (size of the kernel matrix)">m_numExamples</a>);</div>
<div class="line"><a id="l00364" name="l00364"></a><span class="lineno">  364</span>            <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ac8b9a895906060a9d50e13b0523d4255" title="kernel matrix (precomputed matrix or matrix cache)">m_kernelMatrix</a>.row(iv, 0, <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287" title="number of examples in the problem (size of the kernel matrix)">m_numExamples</a>, &amp;q[0]);</div>
<div class="line"><a id="l00365" name="l00365"></a><span class="lineno">  365</span> </div>
<div class="line"><a id="l00366" name="l00366"></a><span class="lineno">  366</span>            <span class="keywordflow">for</span> (std::size_t a = 0; a != <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287" title="number of examples in the problem (size of the kernel matrix)">m_numExamples</a>; a++)</div>
<div class="line"><a id="l00367" name="l00367"></a><span class="lineno">  367</span>            {</div>
<div class="line"><a id="l00368" name="l00368"></a><span class="lineno">  368</span>                <span class="keywordtype">double</span> k = q[a];</div>
<div class="line"><a id="l00369" name="l00369"></a><span class="lineno">  369</span>                <a class="code hl_struct" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html" title="data structure describing one training example">Example</a>&amp; ex = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[a];</div>
<div class="line"><a id="l00370" name="l00370"></a><span class="lineno">  370</span>                <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_qp_sparse_array_1_1_row.html" title="Data structure describing a row of the sparse array.">QpSparseArray&lt;QpFloatType&gt;::Row</a> <span class="keyword">const</span>&amp; row = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a7b64dccd47c7db2a9fa4110b55b52c7c" title="kernel modifiers">m_M</a>.row(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4b3c753187efbb58b433a76face7a52d" title="number of classes in the problem">m_classes</a> * r + ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a289bed9316066dd53203df71f2bfb767" title="label of this example">y</a>);</div>
<div class="line"><a id="l00371" name="l00371"></a><span class="lineno">  371</span>                <a class="code hl_typedef" href="classshark_1_1_qp_mc_simplex_decomp.html#ac2dfe25a10f0c19a059d4a5625a19937">QpFloatType</a> def = row.defaultvalue;</div>
<div class="line"><a id="l00372" name="l00372"></a><span class="lineno">  372</span>                <span class="keywordflow">for</span> (std::size_t b=0; b&lt;row.size; b++)</div>
<div class="line"><a id="l00373" name="l00373"></a><span class="lineno">  373</span>                {</div>
<div class="line"><a id="l00374" name="l00374"></a><span class="lineno">  374</span>                    std::size_t f = ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ae8e200b285451dd8bfb99672e23984b4" title="list of all m_cardP variables, in order of the p-index">var</a>[row.entry[b].index];</div>
<div class="line"><a id="l00375" name="l00375"></a><span class="lineno">  375</span>                    <span class="keywordflow">if</span> (f &gt;= <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a>) </div>
<div class="line"><a id="l00376" name="l00376"></a><span class="lineno">  376</span>                        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(f) -= mu * (row.entry[b].value - def) * k;</div>
<div class="line"><a id="l00377" name="l00377"></a><span class="lineno">  377</span>                }</div>
<div class="line"><a id="l00378" name="l00378"></a><span class="lineno">  378</span>                <span class="keywordflow">if</span> (def != 0.0)</div>
<div class="line"><a id="l00379" name="l00379"></a><span class="lineno">  379</span>                {</div>
<div class="line"><a id="l00380" name="l00380"></a><span class="lineno">  380</span>                    <span class="keywordtype">double</span> upd = mu * def * k;</div>
<div class="line"><a id="l00381" name="l00381"></a><span class="lineno">  381</span>                    <span class="keywordflow">for</span> (std::size_t  b=ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aed59b679c1979d9f8ed433f5f56716ab" title="number of active variables">active</a>; b&lt;<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>; b++)</div>
<div class="line"><a id="l00382" name="l00382"></a><span class="lineno">  382</span>                    {</div>
<div class="line"><a id="l00383" name="l00383"></a><span class="lineno">  383</span>                        std::size_t f = ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[b];</div>
<div class="line"><a id="l00384" name="l00384"></a><span class="lineno">  384</span>                        <a class="code hl_define" href="_exception_8h.html#a73abb5049a0168d72a48e72dda41708b">SHARK_ASSERT</a>(f &gt;= <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a>);</div>
<div class="line"><a id="l00385" name="l00385"></a><span class="lineno">  385</span>                        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(f) -= upd;</div>
<div class="line"><a id="l00386" name="l00386"></a><span class="lineno">  386</span>                    }</div>
<div class="line"><a id="l00387" name="l00387"></a><span class="lineno">  387</span>                }</div>
<div class="line"><a id="l00388" name="l00388"></a><span class="lineno">  388</span>            }</div>
<div class="line"><a id="l00389" name="l00389"></a><span class="lineno">  389</span>        }</div>
<div class="line"><a id="l00390" name="l00390"></a><span class="lineno">  390</span> </div>
<div class="line"><a id="l00391" name="l00391"></a><span class="lineno">  391</span>        <span class="keywordflow">for</span> (std::size_t  i=0; i&lt;<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287" title="number of examples in the problem (size of the kernel matrix)">m_numExamples</a>; i++) </div>
<div class="line"><a id="l00392" name="l00392"></a><span class="lineno">  392</span>            <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i].active = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>;</div>
<div class="line"><a id="l00393" name="l00393"></a><span class="lineno">  393</span>        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a> = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287" title="number of examples in the problem (size of the kernel matrix)">m_numExamples</a>;</div>
<div class="line"><a id="l00394" name="l00394"></a><span class="lineno">  394</span>        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a> = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>;</div>
<div class="line"><a id="l00395" name="l00395"></a><span class="lineno">  395</span>    }</div>
</div>
<div class="line"><a id="l00396" name="l00396"></a><span class="lineno">  396</span>    <span class="comment"></span></div>
<div class="line"><a id="l00397" name="l00397"></a><span class="lineno">  397</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00398" name="l00398"></a><span class="lineno">  398</span><span class="comment">    /// \brief select the working set</span></div>
<div class="line"><a id="l00399" name="l00399"></a><span class="lineno">  399</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00400" name="l00400"></a><span class="lineno">  400</span><span class="comment">    /// Select one or two numVariables for the sub-problem</span></div>
<div class="line"><a id="l00401" name="l00401"></a><span class="lineno">  401</span><span class="comment">    /// and return the maximal KKT violation. The method</span></div>
<div class="line"><a id="l00402" name="l00402"></a><span class="lineno">  402</span><span class="comment">    /// MAY select the same index for i and j. In that</span></div>
<div class="line"><a id="l00403" name="l00403"></a><span class="lineno">  403</span><span class="comment">    /// case the working set consists of a single variables.</span></div>
<div class="line"><a id="l00404" name="l00404"></a><span class="lineno">  404</span><span class="comment">    /// The working set may be invalid if the method reports</span></div>
<div class="line"><a id="l00405" name="l00405"></a><span class="lineno">  405</span><span class="comment">    /// a KKT violation of zero, indicating optimality. </span></div>
<div class="foldopen" id="foldopen00406" data-start="{" data-end="}">
<div class="line"><a id="l00406" name="l00406"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a8304e5a2955859682a416bc28c3d743f">  406</a></span><span class="comment"></span>    <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a8304e5a2955859682a416bc28c3d743f" title="select the working set">selectWorkingSet</a>(std::size_t&amp; i, std::size_t&amp; j)</div>
<div class="line"><a id="l00407" name="l00407"></a><span class="lineno">  407</span>    {</div>
<div class="line"><a id="l00408" name="l00408"></a><span class="lineno">  408</span>        </div>
<div class="line"><a id="l00409" name="l00409"></a><span class="lineno">  409</span>        <span class="comment">//first order selection</span></div>
<div class="line"><a id="l00410" name="l00410"></a><span class="lineno">  410</span>        <span class="comment">//we select the best variable along the box constraint (for a step between samples)</span></div>
<div class="line"><a id="l00411" name="l00411"></a><span class="lineno">  411</span>        <span class="comment">//and the best gradient and example index for a step along the simplex (step inside a sample)</span></div>
<div class="line"><a id="l00412" name="l00412"></a><span class="lineno">  412</span>        <span class="keywordtype">double</span> maxGradient = 0;<span class="comment">//max gradient for variables between samples (box constraints)</span></div>
<div class="line"><a id="l00413" name="l00413"></a><span class="lineno">  413</span>        <span class="keywordtype">double</span> maxSimplexGradient = 0;<span class="comment">//max gradient along the simplex constraints</span></div>
<div class="line"><a id="l00414" name="l00414"></a><span class="lineno">  414</span>        std::size_t maxSimplexExample = 0;<span class="comment">//example with the maximum simplex constraint</span></div>
<div class="line"><a id="l00415" name="l00415"></a><span class="lineno">  415</span>        i = j = 0;</div>
<div class="line"><a id="l00416" name="l00416"></a><span class="lineno">  416</span>        <span class="comment">// first order selection</span></div>
<div class="line"><a id="l00417" name="l00417"></a><span class="lineno">  417</span>        <span class="keywordflow">for</span> (std::size_t e=0; e&lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>; e++)</div>
<div class="line"><a id="l00418" name="l00418"></a><span class="lineno">  418</span>        {</div>
<div class="line"><a id="l00419" name="l00419"></a><span class="lineno">  419</span>            <a class="code hl_struct" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html" title="data structure describing one training example">Example</a>&amp; ex = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[e];</div>
<div class="line"><a id="l00420" name="l00420"></a><span class="lineno">  420</span>            <span class="keywordtype">bool</span> canGrow = ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ac5aea03b47634b4edeaf71099548433c" title="total sum of all variables of this example">varsum</a> &lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>;</div>
<div class="line"><a id="l00421" name="l00421"></a><span class="lineno">  421</span>            </div>
<div class="line"><a id="l00422" name="l00422"></a><span class="lineno">  422</span>            <span class="comment">//calculate the maximum violationg pair for the example.</span></div>
<div class="line"><a id="l00423" name="l00423"></a><span class="lineno">  423</span>            std::pair&lt;std::pair&lt;double,std::size_t&gt;,std::pair&lt;double,std::size_t&gt; &gt; pair = <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#abed9aa58f4c24140ba445737987a6f98" title="For a given simplex returns the MVP indicies (max_up,min_down)">getSimplexMVP</a>(ex);</div>
<div class="line"><a id="l00424" name="l00424"></a><span class="lineno">  424</span>            <span class="keywordtype">double</span> up = pair.first.first;</div>
<div class="line"><a id="l00425" name="l00425"></a><span class="lineno">  425</span>            <span class="keywordtype">double</span> down = pair.second.first;</div>
<div class="line"><a id="l00426" name="l00426"></a><span class="lineno">  426</span>            </div>
<div class="line"><a id="l00427" name="l00427"></a><span class="lineno">  427</span>            <span class="keywordflow">if</span>(!canGrow &amp;&amp; up - down &gt; maxSimplexGradient){</div>
<div class="line"><a id="l00428" name="l00428"></a><span class="lineno">  428</span>                maxSimplexGradient = up-down;</div>
<div class="line"><a id="l00429" name="l00429"></a><span class="lineno">  429</span>                maxSimplexExample = e;</div>
<div class="line"><a id="l00430" name="l00430"></a><span class="lineno">  430</span>            }</div>
<div class="line"><a id="l00431" name="l00431"></a><span class="lineno">  431</span>            <span class="keywordflow">if</span> (canGrow &amp;&amp; up &gt; maxGradient) {</div>
<div class="line"><a id="l00432" name="l00432"></a><span class="lineno">  432</span>                maxGradient = up;</div>
<div class="line"><a id="l00433" name="l00433"></a><span class="lineno">  433</span>                i = pair.first.second;</div>
<div class="line"><a id="l00434" name="l00434"></a><span class="lineno">  434</span>            }</div>
<div class="line"><a id="l00435" name="l00435"></a><span class="lineno">  435</span>            <span class="keywordflow">if</span> (-down &gt; maxGradient) {</div>
<div class="line"><a id="l00436" name="l00436"></a><span class="lineno">  436</span>                maxGradient = -down;</div>
<div class="line"><a id="l00437" name="l00437"></a><span class="lineno">  437</span>                i = pair.second.second;</div>
<div class="line"><a id="l00438" name="l00438"></a><span class="lineno">  438</span>            }</div>
<div class="line"><a id="l00439" name="l00439"></a><span class="lineno">  439</span>        }</div>
<div class="line"><a id="l00440" name="l00440"></a><span class="lineno">  440</span>        </div>
<div class="line"><a id="l00441" name="l00441"></a><span class="lineno">  441</span>        <span class="comment">//find the best possible partner of the variable</span></div>
<div class="line"><a id="l00442" name="l00442"></a><span class="lineno">  442</span>        <span class="comment">//by searching every other sample</span></div>
<div class="line"><a id="l00443" name="l00443"></a><span class="lineno">  443</span>        std::pair&lt;std::pair&lt;std::size_t,std::size_t&gt; ,<span class="keywordtype">double</span> &gt; boxPair = <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a3689cea409b991cc35f58e8cf23ddc00" title="Finds the second variable of a working set using maximum gain and returns the pair and gain.">maxGainBox</a>(i);</div>
<div class="line"><a id="l00444" name="l00444"></a><span class="lineno">  444</span>        <span class="keywordtype">double</span> bestGain = boxPair.second;</div>
<div class="line"><a id="l00445" name="l00445"></a><span class="lineno">  445</span>        std::pair&lt;std::size_t, std::size_t&gt; best = boxPair.first;</div>
<div class="line"><a id="l00446" name="l00446"></a><span class="lineno">  446</span>        </div>
<div class="line"><a id="l00447" name="l00447"></a><span class="lineno">  447</span>        <span class="comment">//always search the simplex of the variable</span></div>
<div class="line"><a id="l00448" name="l00448"></a><span class="lineno">  448</span>        std::pair&lt;std::pair&lt;std::size_t,std::size_t&gt; ,<span class="keywordtype">double</span> &gt; simplexPairi = <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a190272c5d5f87ebd96e5efe34b7d5614" title="Returns the best variable pair (i,j) and gain for a given example.">maxGainSimplex</a>(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[i].<a class="code hl_namespace" href="namespaceexample.html">example</a>);</div>
<div class="line"><a id="l00449" name="l00449"></a><span class="lineno">  449</span>        <span class="keywordflow">if</span>(simplexPairi.second &gt; bestGain){</div>
<div class="line"><a id="l00450" name="l00450"></a><span class="lineno">  450</span>            best = simplexPairi.first;</div>
<div class="line"><a id="l00451" name="l00451"></a><span class="lineno">  451</span>            bestGain = simplexPairi.second;</div>
<div class="line"><a id="l00452" name="l00452"></a><span class="lineno">  452</span>        }</div>
<div class="line"><a id="l00453" name="l00453"></a><span class="lineno">  453</span>        <span class="comment">//finally search also in the best simplex</span></div>
<div class="line"><a id="l00454" name="l00454"></a><span class="lineno">  454</span>        <span class="keywordflow">if</span>(maxSimplexGradient &gt; 0){</div>
<div class="line"><a id="l00455" name="l00455"></a><span class="lineno">  455</span>            std::pair&lt;std::pair&lt;std::size_t,std::size_t&gt; ,<span class="keywordtype">double</span> &gt; simplexPairBest = <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a190272c5d5f87ebd96e5efe34b7d5614" title="Returns the best variable pair (i,j) and gain for a given example.">maxGainSimplex</a>(maxSimplexExample);</div>
<div class="line"><a id="l00456" name="l00456"></a><span class="lineno">  456</span>            <span class="keywordflow">if</span>(simplexPairBest.second &gt; bestGain){</div>
<div class="line"><a id="l00457" name="l00457"></a><span class="lineno">  457</span>                best = simplexPairBest.first;</div>
<div class="line"><a id="l00458" name="l00458"></a><span class="lineno">  458</span>                bestGain = simplexPairBest.second;</div>
<div class="line"><a id="l00459" name="l00459"></a><span class="lineno">  459</span>            }</div>
<div class="line"><a id="l00460" name="l00460"></a><span class="lineno">  460</span>        }</div>
<div class="line"><a id="l00461" name="l00461"></a><span class="lineno">  461</span>        i = best.first;</div>
<div class="line"><a id="l00462" name="l00462"></a><span class="lineno">  462</span>        j = best.second;</div>
<div class="line"><a id="l00463" name="l00463"></a><span class="lineno">  463</span>        <span class="comment">//return the mvp gradient</span></div>
<div class="line"><a id="l00464" name="l00464"></a><span class="lineno">  464</span>        <span class="keywordflow">return</span> std::max(maxGradient,maxSimplexGradient);</div>
<div class="line"><a id="l00465" name="l00465"></a><span class="lineno">  465</span>    }</div>
</div>
<div class="line"><a id="l00466" name="l00466"></a><span class="lineno">  466</span>    <span class="comment"></span></div>
<div class="line"><a id="l00467" name="l00467"></a><span class="lineno">  467</span><span class="comment">    /// return the largest KKT violation</span></div>
<div class="foldopen" id="foldopen00468" data-start="{" data-end="}">
<div class="line"><a id="l00468" name="l00468"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a62b40d1335f1aa500d790cf6b5e0d735">  468</a></span><span class="comment"></span>    <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a62b40d1335f1aa500d790cf6b5e0d735" title="return the largest KKT violation">checkKKT</a>()<span class="keyword">const</span></div>
<div class="line"><a id="l00469" name="l00469"></a><span class="lineno">  469</span><span class="keyword">    </span>{</div>
<div class="line"><a id="l00470" name="l00470"></a><span class="lineno">  470</span>        <span class="keywordtype">double</span> ret = 0.0;</div>
<div class="line"><a id="l00471" name="l00471"></a><span class="lineno">  471</span>        <span class="keywordflow">for</span> (std::size_t i=0; i&lt;<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>; i++){</div>
<div class="line"><a id="l00472" name="l00472"></a><span class="lineno">  472</span>            <a class="code hl_struct" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html" title="data structure describing one training example">Example</a> <span class="keyword">const</span>&amp; ex = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i];</div>
<div class="line"><a id="l00473" name="l00473"></a><span class="lineno">  473</span>            std::pair&lt;std::pair&lt;double,std::size_t&gt;,std::pair&lt;double,std::size_t&gt; &gt; pair = <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#abed9aa58f4c24140ba445737987a6f98" title="For a given simplex returns the MVP indicies (max_up,min_down)">getSimplexMVP</a>(ex);</div>
<div class="line"><a id="l00474" name="l00474"></a><span class="lineno">  474</span>            <span class="keywordtype">double</span> up = pair.first.first;</div>
<div class="line"><a id="l00475" name="l00475"></a><span class="lineno">  475</span>            <span class="keywordtype">double</span> down = pair.second.first;</div>
<div class="line"><a id="l00476" name="l00476"></a><span class="lineno">  476</span>            </div>
<div class="line"><a id="l00477" name="l00477"></a><span class="lineno">  477</span>            <span class="comment">//check all search directions</span></div>
<div class="line"><a id="l00478" name="l00478"></a><span class="lineno">  478</span>            <span class="comment">//case 1:  decreasing the value of a variable</span></div>
<div class="line"><a id="l00479" name="l00479"></a><span class="lineno">  479</span>            ret = std::max(-down, ret);</div>
<div class="line"><a id="l00480" name="l00480"></a><span class="lineno">  480</span>            <span class="comment">//case 2: if we are not at the boundary increasing the variable</span></div>
<div class="line"><a id="l00481" name="l00481"></a><span class="lineno">  481</span>            <span class="keywordflow">if</span>(ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ac5aea03b47634b4edeaf71099548433c" title="total sum of all variables of this example">varsum</a> &lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>)</div>
<div class="line"><a id="l00482" name="l00482"></a><span class="lineno">  482</span>                ret = std::max(up, ret);</div>
<div class="line"><a id="l00483" name="l00483"></a><span class="lineno">  483</span>            <span class="comment">//case 3: along the plane \sum_i alpha_i = m_C</span></div>
<div class="line"><a id="l00484" name="l00484"></a><span class="lineno">  484</span>            <span class="keywordflow">if</span>(ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ac5aea03b47634b4edeaf71099548433c" title="total sum of all variables of this example">varsum</a> == <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>)</div>
<div class="line"><a id="l00485" name="l00485"></a><span class="lineno">  485</span>                ret = std::max(up-down, ret);</div>
<div class="line"><a id="l00486" name="l00486"></a><span class="lineno">  486</span>        }</div>
<div class="line"><a id="l00487" name="l00487"></a><span class="lineno">  487</span>        <span class="keywordflow">return</span> ret;</div>
<div class="line"><a id="l00488" name="l00488"></a><span class="lineno">  488</span>    }</div>
</div>
<div class="line"><a id="l00489" name="l00489"></a><span class="lineno">  489</span>    </div>
<div class="line"><a id="l00490" name="l00490"></a><span class="lineno">  490</span><span class="keyword">protected</span>:</div>
<div class="line"><a id="l00491" name="l00491"></a><span class="lineno">  491</span>    <span class="comment"></span></div>
<div class="line"><a id="l00492" name="l00492"></a><span class="lineno">  492</span><span class="comment">    /// data structure describing one variable of the problem</span></div>
<div class="foldopen" id="foldopen00493" data-start="{" data-end="};">
<div class="line"><a id="l00493" name="l00493"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_variable.html">  493</a></span><span class="comment"></span>    <span class="keyword">struct </span><a class="code hl_struct" href="structshark_1_1_qp_mc_simplex_decomp_1_1_variable.html" title="data structure describing one variable of the problem">Variable</a></div>
<div class="line"><a id="l00494" name="l00494"></a><span class="lineno">  494</span>    {<span class="comment"></span></div>
<div class="line"><a id="l00495" name="l00495"></a><span class="lineno">  495</span><span class="comment">        ///index into the example list</span></div>
<div class="line"><a id="l00496" name="l00496"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_variable.html#afaea06b9275e9e4efcc583ea48870f39">  496</a></span><span class="comment"></span>        std::size_t <a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_variable.html#afaea06b9275e9e4efcc583ea48870f39" title="index into the example list">example</a>;<span class="comment"></span></div>
<div class="line"><a id="l00497" name="l00497"></a><span class="lineno">  497</span><span class="comment">        /// constraint corresponding to this variable</span></div>
<div class="line"><a id="l00498" name="l00498"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_variable.html#ab28a742507fae39e644ac56ae9db49e1">  498</a></span><span class="comment"></span>        std::size_t <a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_variable.html#ab28a742507fae39e644ac56ae9db49e1" title="constraint corresponding to this variable">p</a>;<span class="comment"></span></div>
<div class="line"><a id="l00499" name="l00499"></a><span class="lineno">  499</span><span class="comment">        /// index into example-&gt;m_numVariables</span></div>
<div class="line"><a id="l00500" name="l00500"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_variable.html#a3d8c24c03e6ba4850200a58764f2ed84">  500</a></span><span class="comment"></span>        std::size_t <a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_variable.html#a3d8c24c03e6ba4850200a58764f2ed84" title="index into example-&gt;m_numVariables">index</a>;<span class="comment"></span></div>
<div class="line"><a id="l00501" name="l00501"></a><span class="lineno">  501</span><span class="comment">        /// diagonal entry of the big Q-matrix</span></div>
<div class="line"><a id="l00502" name="l00502"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_variable.html#a46558dedf8e8f00a5a1dc67cb76783fe">  502</a></span><span class="comment"></span>        <span class="keywordtype">double</span> <a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_variable.html#a46558dedf8e8f00a5a1dc67cb76783fe" title="diagonal entry of the big Q-matrix">diagonal</a>;</div>
<div class="line"><a id="l00503" name="l00503"></a><span class="lineno">  503</span>    };</div>
</div>
<div class="line"><a id="l00504" name="l00504"></a><span class="lineno">  504</span><span class="comment"></span> </div>
<div class="line"><a id="l00505" name="l00505"></a><span class="lineno">  505</span><span class="comment">    /// data structure describing one training example</span></div>
<div class="foldopen" id="foldopen00506" data-start="{" data-end="};">
<div class="line"><a id="l00506" name="l00506"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html">  506</a></span><span class="comment"></span>    <span class="keyword">struct </span><a class="code hl_struct" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html" title="data structure describing one training example">Example</a></div>
<div class="line"><a id="l00507" name="l00507"></a><span class="lineno">  507</span>    {<span class="comment"></span></div>
<div class="line"><a id="l00508" name="l00508"></a><span class="lineno">  508</span><span class="comment">        /// example index in the dataset, not the example vector!</span></div>
<div class="line"><a id="l00509" name="l00509"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aab58acc2d5b87c0fe69188397f97a769">  509</a></span><span class="comment"></span>        std::size_t <a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aab58acc2d5b87c0fe69188397f97a769" title="example index in the dataset, not the example vector!">index</a>;<span class="comment"></span></div>
<div class="line"><a id="l00510" name="l00510"></a><span class="lineno">  510</span><span class="comment">        /// label of this example</span></div>
<div class="line"><a id="l00511" name="l00511"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a289bed9316066dd53203df71f2bfb767">  511</a></span><span class="comment"></span>        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a289bed9316066dd53203df71f2bfb767" title="label of this example">y</a>;<span class="comment"></span></div>
<div class="line"><a id="l00512" name="l00512"></a><span class="lineno">  512</span><span class="comment">        /// number of active variables</span></div>
<div class="line"><a id="l00513" name="l00513"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aed59b679c1979d9f8ed433f5f56716ab">  513</a></span><span class="comment"></span>        std::size_t <a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aed59b679c1979d9f8ed433f5f56716ab" title="number of active variables">active</a>;<span class="comment"></span></div>
<div class="line"><a id="l00514" name="l00514"></a><span class="lineno">  514</span><span class="comment">        /// list of all m_cardP variables, in order of the p-index</span></div>
<div class="line"><a id="l00515" name="l00515"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ae8e200b285451dd8bfb99672e23984b4">  515</a></span><span class="comment"></span>        std::size_t* <a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ae8e200b285451dd8bfb99672e23984b4" title="list of all m_cardP variables, in order of the p-index">var</a>;<span class="comment"></span></div>
<div class="line"><a id="l00516" name="l00516"></a><span class="lineno">  516</span><span class="comment">        /// list of active variables</span></div>
<div class="line"><a id="l00517" name="l00517"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d">  517</a></span><span class="comment"></span>        std::size_t* <a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>;<span class="comment"></span></div>
<div class="line"><a id="l00518" name="l00518"></a><span class="lineno">  518</span><span class="comment">        /// total sum of all variables of this example</span></div>
<div class="line"><a id="l00519" name="l00519"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ac5aea03b47634b4edeaf71099548433c">  519</a></span><span class="comment"></span>        <span class="keywordtype">double</span> <a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ac5aea03b47634b4edeaf71099548433c" title="total sum of all variables of this example">varsum</a>;<span class="comment"></span></div>
<div class="line"><a id="l00520" name="l00520"></a><span class="lineno">  520</span><span class="comment">        /// diagonal entry of the kernel matrix k(x,x);</span></div>
<div class="line"><a id="l00521" name="l00521"></a><span class="lineno"><a class="line" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a695f9e848d59f0ada274e8c18e283678">  521</a></span><span class="comment"></span>        <span class="keywordtype">double</span> <a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a695f9e848d59f0ada274e8c18e283678" title="diagonal entry of the kernel matrix k(x,x);">diagonal</a>;</div>
<div class="line"><a id="l00522" name="l00522"></a><span class="lineno">  522</span>    };</div>
</div>
<div class="line"><a id="l00523" name="l00523"></a><span class="lineno">  523</span>    <span class="comment"></span></div>
<div class="line"><a id="l00524" name="l00524"></a><span class="lineno">  524</span><span class="comment">    /// \brief Finds the second variable of a working set using maximum gain and returns the pair and gain</span></div>
<div class="line"><a id="l00525" name="l00525"></a><span class="lineno">  525</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00526" name="l00526"></a><span class="lineno">  526</span><span class="comment">    /// The variable is searched in-between samples. And not inside the simplex of i.</span></div>
<div class="line"><a id="l00527" name="l00527"></a><span class="lineno">  527</span><span class="comment">    /// It returns the best pair (i,j) as well as the gain. If the first variable</span></div>
<div class="line"><a id="l00528" name="l00528"></a><span class="lineno">  528</span><span class="comment">    /// can&#39;t make a step, gain 0 is returned with pair(i,i).</span></div>
<div class="foldopen" id="foldopen00529" data-start="{" data-end="}">
<div class="line"><a id="l00529" name="l00529"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a3689cea409b991cc35f58e8cf23ddc00">  529</a></span><span class="comment"></span>    std::pair&lt;std::pair&lt;std::size_t,std::size_t&gt;,<span class="keywordtype">double</span>&gt; <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a3689cea409b991cc35f58e8cf23ddc00" title="Finds the second variable of a working set using maximum gain and returns the pair and gain.">maxGainBox</a>(std::size_t i)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00530" name="l00530"></a><span class="lineno">  530</span>        std::size_t e = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[i].example;</div>
<div class="line"><a id="l00531" name="l00531"></a><span class="lineno">  531</span>        <a class="code hl_define" href="_exception_8h.html#a73abb5049a0168d72a48e72dda41708b">SHARK_ASSERT</a>(e &lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>);</div>
<div class="line"><a id="l00532" name="l00532"></a><span class="lineno">  532</span>        std::size_t pi = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[i].p;</div>
<div class="line"><a id="l00533" name="l00533"></a><span class="lineno">  533</span>        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> yi = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[e].y;</div>
<div class="line"><a id="l00534" name="l00534"></a><span class="lineno">  534</span>        <span class="keywordtype">double</span> Qii = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[i].diagonal;</div>
<div class="line"><a id="l00535" name="l00535"></a><span class="lineno">  535</span>        <span class="keywordtype">double</span> gi = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(i);</div>
<div class="line"><a id="l00536" name="l00536"></a><span class="lineno">  536</span>        <span class="keywordflow">if</span>(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[e].varsum == <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a> &amp;&amp; gi &gt; 0)</div>
<div class="line"><a id="l00537" name="l00537"></a><span class="lineno">  537</span>            <span class="keywordflow">return</span> std::make_pair(std::make_pair(i,i),0.0);</div>
<div class="line"><a id="l00538" name="l00538"></a><span class="lineno">  538</span>        </div>
<div class="line"><a id="l00539" name="l00539"></a><span class="lineno">  539</span>        </div>
<div class="line"><a id="l00540" name="l00540"></a><span class="lineno">  540</span>        <a class="code hl_typedef" href="classshark_1_1_qp_mc_simplex_decomp.html#ac2dfe25a10f0c19a059d4a5625a19937">QpFloatType</a>* k = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ac8b9a895906060a9d50e13b0523d4255" title="kernel matrix (precomputed matrix or matrix cache)">m_kernelMatrix</a>.row(e, 0, <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>);</div>
<div class="line"><a id="l00541" name="l00541"></a><span class="lineno">  541</span>        </div>
<div class="line"><a id="l00542" name="l00542"></a><span class="lineno">  542</span>        std::size_t bestj = i;</div>
<div class="line"><a id="l00543" name="l00543"></a><span class="lineno">  543</span>        <span class="keywordtype">double</span> bestGain = gi * gi / Qii;</div>
<div class="line"><a id="l00544" name="l00544"></a><span class="lineno">  544</span>        </div>
<div class="line"><a id="l00545" name="l00545"></a><span class="lineno">  545</span>        <span class="keywordflow">for</span> (std::size_t a=0; a&lt;<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>; a++)</div>
<div class="line"><a id="l00546" name="l00546"></a><span class="lineno">  546</span>        {</div>
<div class="line"><a id="l00547" name="l00547"></a><span class="lineno">  547</span>            <span class="comment">//don&#39;t search the simplex of the first variable</span></div>
<div class="line"><a id="l00548" name="l00548"></a><span class="lineno">  548</span>            <span class="keywordflow">if</span>(a == e) <span class="keywordflow">continue</span>;</div>
<div class="line"><a id="l00549" name="l00549"></a><span class="lineno">  549</span>            </div>
<div class="line"><a id="l00550" name="l00550"></a><span class="lineno">  550</span>            <a class="code hl_struct" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html" title="data structure describing one training example">Example</a> <span class="keyword">const</span>&amp; exa = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[a];</div>
<div class="line"><a id="l00551" name="l00551"></a><span class="lineno">  551</span>            <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> ya = exa.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a289bed9316066dd53203df71f2bfb767" title="label of this example">y</a>;</div>
<div class="line"><a id="l00552" name="l00552"></a><span class="lineno">  552</span>            <span class="keywordtype">bool</span> canGrow = exa.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ac5aea03b47634b4edeaf71099548433c" title="total sum of all variables of this example">varsum</a> != <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>;</div>
<div class="line"><a id="l00553" name="l00553"></a><span class="lineno">  553</span>            </div>
<div class="line"><a id="l00554" name="l00554"></a><span class="lineno">  554</span>            <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_qp_sparse_array_1_1_row.html" title="Data structure describing a row of the sparse array.">QpSparseArray&lt;QpFloatType&gt;::Row</a> <span class="keyword">const</span>&amp; row = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a7b64dccd47c7db2a9fa4110b55b52c7c" title="kernel modifiers">m_M</a>.row(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4b3c753187efbb58b433a76face7a52d" title="number of classes in the problem">m_classes</a> * (yi * <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a> + pi) + ya);</div>
<div class="line"><a id="l00555" name="l00555"></a><span class="lineno">  555</span>            <a class="code hl_typedef" href="classshark_1_1_qp_mc_simplex_decomp.html#ac2dfe25a10f0c19a059d4a5625a19937">QpFloatType</a> def = row.defaultvalue;</div>
<div class="line"><a id="l00556" name="l00556"></a><span class="lineno">  556</span>            </div>
<div class="line"><a id="l00557" name="l00557"></a><span class="lineno">  557</span>            <span class="keywordflow">for</span> (std::size_t p=0, b=0; p &lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>; p++)</div>
<div class="line"><a id="l00558" name="l00558"></a><span class="lineno">  558</span>            {</div>
<div class="line"><a id="l00559" name="l00559"></a><span class="lineno">  559</span>                std::size_t j = exa.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ae8e200b285451dd8bfb99672e23984b4" title="list of all m_cardP variables, in order of the p-index">var</a>[p];</div>
<div class="line"><a id="l00560" name="l00560"></a><span class="lineno">  560</span>                </div>
<div class="line"><a id="l00561" name="l00561"></a><span class="lineno">  561</span>                <span class="keywordtype">double</span> Qjj = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[j].diagonal;</div>
<div class="line"><a id="l00562" name="l00562"></a><span class="lineno">  562</span>                <span class="keywordtype">double</span> gj = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(j);</div>
<div class="line"><a id="l00563" name="l00563"></a><span class="lineno">  563</span>                <span class="keywordtype">double</span> Qij = def * k[a];</div>
<div class="line"><a id="l00564" name="l00564"></a><span class="lineno">  564</span>                <span class="comment">//check whether we are at an existing element of the sparse row</span></div>
<div class="line"><a id="l00565" name="l00565"></a><span class="lineno">  565</span>                <span class="keywordflow">if</span>( b != row.size &amp;&amp; p == row.entry[b].index){</div>
<div class="line"><a id="l00566" name="l00566"></a><span class="lineno">  566</span>                    Qij = row.entry[b].value * k[a];</div>
<div class="line"><a id="l00567" name="l00567"></a><span class="lineno">  567</span>                    ++b;<span class="comment">//move to next element</span></div>
<div class="line"><a id="l00568" name="l00568"></a><span class="lineno">  568</span>                }</div>
<div class="line"><a id="l00569" name="l00569"></a><span class="lineno">  569</span>                </div>
<div class="line"><a id="l00570" name="l00570"></a><span class="lineno">  570</span>                <span class="comment">//don&#39;t check variables which are shrinked or bounded</span></div>
<div class="line"><a id="l00571" name="l00571"></a><span class="lineno">  571</span>                <span class="keywordflow">if</span>(j &gt;= <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a> || (<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(j) == 0 &amp;&amp; gj &lt;= 0)|| (!canGrow &amp;&amp; gj &gt;= 0))</div>
<div class="line"><a id="l00572" name="l00572"></a><span class="lineno">  572</span>                    <span class="keywordflow">continue</span>;</div>
<div class="line"><a id="l00573" name="l00573"></a><span class="lineno">  573</span>                </div>
<div class="line"><a id="l00574" name="l00574"></a><span class="lineno">  574</span>                <span class="keywordtype">double</span> gain = detail::maximumGainQuadratic2D(Qii, Qjj, Qij, gi,gj);</div>
<div class="line"><a id="l00575" name="l00575"></a><span class="lineno">  575</span>                <span class="keywordflow">if</span>( bestGain &lt; gain){</div>
<div class="line"><a id="l00576" name="l00576"></a><span class="lineno">  576</span>                    bestj = j;</div>
<div class="line"><a id="l00577" name="l00577"></a><span class="lineno">  577</span>                    bestGain = gain;</div>
<div class="line"><a id="l00578" name="l00578"></a><span class="lineno">  578</span>                }</div>
<div class="line"><a id="l00579" name="l00579"></a><span class="lineno">  579</span>            }</div>
<div class="line"><a id="l00580" name="l00580"></a><span class="lineno">  580</span>        }</div>
<div class="line"><a id="l00581" name="l00581"></a><span class="lineno">  581</span>        <span class="keywordflow">return</span> std::make_pair(std::make_pair(i,bestj),bestGain);</div>
<div class="line"><a id="l00582" name="l00582"></a><span class="lineno">  582</span>    }</div>
</div>
<div class="line"><a id="l00583" name="l00583"></a><span class="lineno">  583</span>    <span class="comment"></span></div>
<div class="line"><a id="l00584" name="l00584"></a><span class="lineno">  584</span><span class="comment">    ///\brief Returns the best variable pair (i,j) and gain for a given example.</span></div>
<div class="line"><a id="l00585" name="l00585"></a><span class="lineno">  585</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00586" name="l00586"></a><span class="lineno">  586</span><span class="comment">    /// For a given example all possible pairs of variables are checkd and the one giving</span></div>
<div class="line"><a id="l00587" name="l00587"></a><span class="lineno">  587</span><span class="comment">    /// the maximum gain is returned. This method has a special handling for the</span></div>
<div class="line"><a id="l00588" name="l00588"></a><span class="lineno">  588</span><span class="comment">    /// simplex case.</span></div>
<div class="foldopen" id="foldopen00589" data-start="{" data-end="}">
<div class="line"><a id="l00589" name="l00589"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a190272c5d5f87ebd96e5efe34b7d5614">  589</a></span><span class="comment"></span>    std::pair&lt;std::pair&lt;std::size_t,std::size_t&gt;,<span class="keywordtype">double</span>&gt; <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a190272c5d5f87ebd96e5efe34b7d5614" title="Returns the best variable pair (i,j) and gain for a given example.">maxGainSimplex</a>(std::size_t e)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00590" name="l00590"></a><span class="lineno">  590</span>        <a class="code hl_struct" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html" title="data structure describing one training example">Example</a> <span class="keyword">const</span>&amp; ex = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[e];</div>
<div class="line"><a id="l00591" name="l00591"></a><span class="lineno">  591</span>        std::size_t pc = ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aed59b679c1979d9f8ed433f5f56716ab" title="number of active variables">active</a>;<span class="comment">//number of active variables for this example</span></div>
<div class="line"><a id="l00592" name="l00592"></a><span class="lineno">  592</span>        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> y = ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a289bed9316066dd53203df71f2bfb767" title="label of this example">y</a>;<span class="comment">//label of the example</span></div>
<div class="line"><a id="l00593" name="l00593"></a><span class="lineno">  593</span>        <span class="keywordtype">bool</span> canGrow = ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ac5aea03b47634b4edeaf71099548433c" title="total sum of all variables of this example">varsum</a> &lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>; <span class="comment">//are we inside the simplex?</span></div>
<div class="line"><a id="l00594" name="l00594"></a><span class="lineno">  594</span>        <span class="keywordtype">double</span> Qee = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[e].diagonal; <span class="comment">//kernel entry of the example</span></div>
<div class="line"><a id="l00595" name="l00595"></a><span class="lineno">  595</span>        </div>
<div class="line"><a id="l00596" name="l00596"></a><span class="lineno">  596</span>        <span class="keywordtype">double</span> bestGain = -1e100;</div>
<div class="line"><a id="l00597" name="l00597"></a><span class="lineno">  597</span>        std::size_t besti = 0;</div>
<div class="line"><a id="l00598" name="l00598"></a><span class="lineno">  598</span>        std::size_t bestj = 0;</div>
<div class="line"><a id="l00599" name="l00599"></a><span class="lineno">  599</span>        </div>
<div class="line"><a id="l00600" name="l00600"></a><span class="lineno">  600</span>        <span class="comment">//search through all possible variable pairs</span></div>
<div class="line"><a id="l00601" name="l00601"></a><span class="lineno">  601</span>        <span class="comment">//for every pair we will build the quadratic subproblem </span></div>
<div class="line"><a id="l00602" name="l00602"></a><span class="lineno">  602</span>        <span class="comment">//and than decide whether we can do </span></div>
<div class="line"><a id="l00603" name="l00603"></a><span class="lineno">  603</span>        <span class="comment">// 1.a valid step in the inside of the simplex</span></div>
<div class="line"><a id="l00604" name="l00604"></a><span class="lineno">  604</span>        <span class="comment">// that is canGrow==true or the gradients of both variables point inside</span></div>
<div class="line"><a id="l00605" name="l00605"></a><span class="lineno">  605</span>        <span class="comment">// 2. a valid step along the simplex constraint, </span></div>
<div class="line"><a id="l00606" name="l00606"></a><span class="lineno">  606</span>        <span class="comment">// that is cangrow == true and both variables point outside)</span></div>
<div class="line"><a id="l00607" name="l00607"></a><span class="lineno">  607</span>        <span class="comment">// 3. a 1-D step</span></div>
<div class="line"><a id="l00608" name="l00608"></a><span class="lineno">  608</span>        <span class="comment">// that is canGrow == true or alpha(i) &gt; 0 &amp; gradient(i) &lt; 0</span></div>
<div class="line"><a id="l00609" name="l00609"></a><span class="lineno">  609</span>        </div>
<div class="line"><a id="l00610" name="l00610"></a><span class="lineno">  610</span>        <span class="comment">//iterate over the active ones as the first variable</span></div>
<div class="line"><a id="l00611" name="l00611"></a><span class="lineno">  611</span>        <span class="keywordflow">for</span>(std::size_t p1 = 0; p1 != pc; ++p1){</div>
<div class="line"><a id="l00612" name="l00612"></a><span class="lineno">  612</span>            std::size_t i = ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[p1];</div>
<div class="line"><a id="l00613" name="l00613"></a><span class="lineno">  613</span>            <span class="keywordtype">double</span> gi = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(i);</div>
<div class="line"><a id="l00614" name="l00614"></a><span class="lineno">  614</span>            <span class="keywordtype">double</span> ai = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(i);</div>
<div class="line"><a id="l00615" name="l00615"></a><span class="lineno">  615</span>            <span class="keywordtype">double</span> Qii = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[i].diagonal;</div>
<div class="line"><a id="l00616" name="l00616"></a><span class="lineno">  616</span>            </div>
<div class="line"><a id="l00617" name="l00617"></a><span class="lineno">  617</span>            <span class="comment">//check whether a 1-D gain is possible</span></div>
<div class="line"><a id="l00618" name="l00618"></a><span class="lineno">  618</span>            <span class="keywordflow">if</span>((gi &lt; 0 &amp;&amp; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(i) &gt; 0.0) || (gi &gt; 0 &amp;&amp; canGrow)){</div>
<div class="line"><a id="l00619" name="l00619"></a><span class="lineno">  619</span>                <span class="keywordtype">double</span> gain = gi * gi / Qii;</div>
<div class="line"><a id="l00620" name="l00620"></a><span class="lineno">  620</span>                <span class="keywordflow">if</span>(gain &gt; bestGain){</div>
<div class="line"><a id="l00621" name="l00621"></a><span class="lineno">  621</span>                    bestGain= gain;</div>
<div class="line"><a id="l00622" name="l00622"></a><span class="lineno">  622</span>                    besti = i;</div>
<div class="line"><a id="l00623" name="l00623"></a><span class="lineno">  623</span>                    bestj = i;</div>
<div class="line"><a id="l00624" name="l00624"></a><span class="lineno">  624</span>                }</div>
<div class="line"><a id="l00625" name="l00625"></a><span class="lineno">  625</span>            }</div>
<div class="line"><a id="l00626" name="l00626"></a><span class="lineno">  626</span>            </div>
<div class="line"><a id="l00627" name="l00627"></a><span class="lineno">  627</span>            <span class="comment">//now create the 2D problem for all possible variable pairs</span></div>
<div class="line"><a id="l00628" name="l00628"></a><span class="lineno">  628</span>            <span class="comment">//and than check for possible gain steps</span></div>
<div class="line"><a id="l00629" name="l00629"></a><span class="lineno">  629</span>            <span class="comment">//find first the row of coefficients for M(y,y,i,j) for all j</span></div>
<div class="line"><a id="l00630" name="l00630"></a><span class="lineno">  630</span>            <span class="comment">//question: is p1 == m_variables[ex.avar[p1]].p?</span></div>
<div class="line"><a id="l00631" name="l00631"></a><span class="lineno">  631</span>            <span class="comment">//otherwise: is p1 == m_variables[ex.var[p1]].p for *all* variables?</span></div>
<div class="line"><a id="l00632" name="l00632"></a><span class="lineno">  632</span>            <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_qp_sparse_array_1_1_row.html" title="Data structure describing a row of the sparse array.">QpSparseArray&lt;QpFloatType&gt;::Row</a> <span class="keyword">const</span>&amp; row = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a7b64dccd47c7db2a9fa4110b55b52c7c" title="kernel modifiers">m_M</a>.row(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4b3c753187efbb58b433a76face7a52d" title="number of classes in the problem">m_classes</a> * (y * <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a> + <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[i].p) + y);</div>
<div class="line"><a id="l00633" name="l00633"></a><span class="lineno">  633</span>            <a class="code hl_typedef" href="classshark_1_1_qp_mc_simplex_decomp.html#ac2dfe25a10f0c19a059d4a5625a19937">QpFloatType</a> def = row.defaultvalue;</div>
<div class="line"><a id="l00634" name="l00634"></a><span class="lineno">  634</span>            </div>
<div class="line"><a id="l00635" name="l00635"></a><span class="lineno">  635</span>            <span class="comment">//we need to iterate over all vars instead of only the active variables to be in sync with the matrix row</span></div>
<div class="line"><a id="l00636" name="l00636"></a><span class="lineno">  636</span>            <span class="comment">//we will still overstep all inactive variables</span></div>
<div class="line"><a id="l00637" name="l00637"></a><span class="lineno">  637</span>            <span class="keywordflow">for</span>(std::size_t p2 = 0, b=0; p2 != <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>; ++p2){</div>
<div class="line"><a id="l00638" name="l00638"></a><span class="lineno">  638</span>                std::size_t j = ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ae8e200b285451dd8bfb99672e23984b4" title="list of all m_cardP variables, in order of the p-index">var</a>[p2];</div>
<div class="line"><a id="l00639" name="l00639"></a><span class="lineno">  639</span>                <span class="keywordtype">double</span> gj = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(j);</div>
<div class="line"><a id="l00640" name="l00640"></a><span class="lineno">  640</span>                <span class="keywordtype">double</span> aj = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(j);</div>
<div class="line"><a id="l00641" name="l00641"></a><span class="lineno">  641</span>                <span class="keywordtype">double</span> Qjj = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[j].diagonal;</div>
<div class="line"><a id="l00642" name="l00642"></a><span class="lineno">  642</span>                </div>
<div class="line"><a id="l00643" name="l00643"></a><span class="lineno">  643</span>                <span class="comment">//create the offdiagonal element of the 2D problem</span></div>
<div class="line"><a id="l00644" name="l00644"></a><span class="lineno">  644</span>                <span class="keywordtype">double</span> Qij = def * Qee;</div>
<div class="line"><a id="l00645" name="l00645"></a><span class="lineno">  645</span>                <span class="comment">//check whether we are at an existing element of the sparse row</span></div>
<div class="line"><a id="l00646" name="l00646"></a><span class="lineno">  646</span>                <span class="keywordflow">if</span>( b != row.size &amp;&amp; p2 == row.entry[b].index){</div>
<div class="line"><a id="l00647" name="l00647"></a><span class="lineno">  647</span>                    Qij = row.entry[b].value * Qee;</div>
<div class="line"><a id="l00648" name="l00648"></a><span class="lineno">  648</span>                    ++b;<span class="comment">//move to next element</span></div>
<div class="line"><a id="l00649" name="l00649"></a><span class="lineno">  649</span>                }</div>
<div class="line"><a id="l00650" name="l00650"></a><span class="lineno">  650</span>                </div>
<div class="line"><a id="l00651" name="l00651"></a><span class="lineno">  651</span>                <span class="comment">//ignore inactive variables or variables we already checked</span></div>
<div class="line"><a id="l00652" name="l00652"></a><span class="lineno">  652</span>                <span class="keywordflow">if</span>(j &gt;= <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a> || j &lt;= i ){</div>
<div class="line"><a id="l00653" name="l00653"></a><span class="lineno">  653</span>                    <span class="keywordflow">continue</span>;</div>
<div class="line"><a id="l00654" name="l00654"></a><span class="lineno">  654</span>                }</div>
<div class="line"><a id="l00655" name="l00655"></a><span class="lineno">  655</span>                </div>
<div class="line"><a id="l00656" name="l00656"></a><span class="lineno">  656</span>                <span class="keywordtype">double</span> gain = 0;</div>
<div class="line"><a id="l00657" name="l00657"></a><span class="lineno">  657</span>                <span class="comment">//check whether we can move along the simplex constraint</span></div>
<div class="line"><a id="l00658" name="l00658"></a><span class="lineno">  658</span>                <span class="keywordflow">if</span>(!canGrow &amp;&amp; gi &gt; 0 &amp;&amp; gj &gt; 0){</div>
<div class="line"><a id="l00659" name="l00659"></a><span class="lineno">  659</span>                    <span class="keywordtype">double</span> gainUp = 0;</div>
<div class="line"><a id="l00660" name="l00660"></a><span class="lineno">  660</span>                    <span class="keywordtype">double</span> gainDown = 0;</div>
<div class="line"><a id="l00661" name="l00661"></a><span class="lineno">  661</span>                    <span class="comment">//we need to check both search directions for ai</span></div>
<div class="line"><a id="l00662" name="l00662"></a><span class="lineno">  662</span>                    <span class="keywordflow">if</span>(aj &gt; 0 &amp;&amp; gi-gj &gt; 0){</div>
<div class="line"><a id="l00663" name="l00663"></a><span class="lineno">  663</span>                        gainUp = detail::maximumGainQuadratic2DOnLine(Qii, Qjj, Qij, gi,gj);</div>
<div class="line"><a id="l00664" name="l00664"></a><span class="lineno">  664</span>                    }</div>
<div class="line"><a id="l00665" name="l00665"></a><span class="lineno">  665</span>                    <span class="comment">//also check whether a line search in the other direction works</span></div>
<div class="line"><a id="l00666" name="l00666"></a><span class="lineno">  666</span>                    <span class="keywordflow">if</span> (ai &gt; 0 &amp;&amp;gj-gi &gt; 0){</div>
<div class="line"><a id="l00667" name="l00667"></a><span class="lineno">  667</span>                        gainDown = detail::maximumGainQuadratic2DOnLine(Qjj, Qii, Qij, gj,gi);</div>
<div class="line"><a id="l00668" name="l00668"></a><span class="lineno">  668</span>                    }</div>
<div class="line"><a id="l00669" name="l00669"></a><span class="lineno">  669</span>                    gain = std::max(gainUp,gainDown);</div>
<div class="line"><a id="l00670" name="l00670"></a><span class="lineno">  670</span>                }</div>
<div class="line"><a id="l00671" name="l00671"></a><span class="lineno">  671</span>                <span class="comment">//else we are inside the simplex</span></div>
<div class="line"><a id="l00672" name="l00672"></a><span class="lineno">  672</span>                <span class="comment">//in this case only check that both variables can shrink if needed</span></div>
<div class="line"><a id="l00673" name="l00673"></a><span class="lineno">  673</span>                <span class="keywordflow">else</span> <span class="keywordflow">if</span>(!(gi &lt;= 0 &amp;&amp; ai == 0) &amp;&amp; !(gj&lt;= 0  &amp;&amp; aj == 0)){</div>
<div class="line"><a id="l00674" name="l00674"></a><span class="lineno">  674</span>                    gain = detail::maximumGainQuadratic2D(Qii, Qjj, Qij, gi,gj);</div>
<div class="line"><a id="l00675" name="l00675"></a><span class="lineno">  675</span>                }</div>
<div class="line"><a id="l00676" name="l00676"></a><span class="lineno">  676</span>                </div>
<div class="line"><a id="l00677" name="l00677"></a><span class="lineno">  677</span>                <span class="comment">//accept only maximum gain</span></div>
<div class="line"><a id="l00678" name="l00678"></a><span class="lineno">  678</span>                <span class="keywordflow">if</span>(gain &gt; bestGain){</div>
<div class="line"><a id="l00679" name="l00679"></a><span class="lineno">  679</span>                    bestGain= gain;</div>
<div class="line"><a id="l00680" name="l00680"></a><span class="lineno">  680</span>                    besti = i;</div>
<div class="line"><a id="l00681" name="l00681"></a><span class="lineno">  681</span>                    bestj = j;</div>
<div class="line"><a id="l00682" name="l00682"></a><span class="lineno">  682</span>                }</div>
<div class="line"><a id="l00683" name="l00683"></a><span class="lineno">  683</span>                </div>
<div class="line"><a id="l00684" name="l00684"></a><span class="lineno">  684</span>            }</div>
<div class="line"><a id="l00685" name="l00685"></a><span class="lineno">  685</span>        }</div>
<div class="line"><a id="l00686" name="l00686"></a><span class="lineno">  686</span>        <span class="comment">//return best pair and possible gain</span></div>
<div class="line"><a id="l00687" name="l00687"></a><span class="lineno">  687</span>        <span class="keywordflow">return</span> std::make_pair(std::make_pair(besti,bestj),bestGain);</div>
<div class="line"><a id="l00688" name="l00688"></a><span class="lineno">  688</span>    }</div>
</div>
<div class="line"><a id="l00689" name="l00689"></a><span class="lineno">  689</span>    <span class="comment"></span></div>
<div class="line"><a id="l00690" name="l00690"></a><span class="lineno">  690</span><span class="comment">    /// \brief For a given simplex returns the MVP indicies (max_up,min_down)</span></div>
<div class="line"><a id="l00691" name="l00691"></a><span class="lineno">  691</span><span class="comment"></span>    std::pair&lt;</div>
<div class="line"><a id="l00692" name="l00692"></a><span class="lineno">  692</span>        std::pair&lt;double,std::size_t&gt;,</div>
<div class="line"><a id="l00693" name="l00693"></a><span class="lineno">  693</span>        std::pair&lt;double,std::size_t&gt; </div>
<div class="foldopen" id="foldopen00694" data-start="{" data-end="}">
<div class="line"><a id="l00694" name="l00694"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#abed9aa58f4c24140ba445737987a6f98">  694</a></span>    &gt; <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#abed9aa58f4c24140ba445737987a6f98" title="For a given simplex returns the MVP indicies (max_up,min_down)">getSimplexMVP</a>(<a class="code hl_struct" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html" title="data structure describing one training example">Example</a> <span class="keyword">const</span>&amp; ex)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00695" name="l00695"></a><span class="lineno">  695</span>        std::size_t pc = ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aed59b679c1979d9f8ed433f5f56716ab" title="number of active variables">active</a>;</div>
<div class="line"><a id="l00696" name="l00696"></a><span class="lineno">  696</span>        <span class="keywordtype">double</span> up = -1e100;</div>
<div class="line"><a id="l00697" name="l00697"></a><span class="lineno">  697</span>        <span class="keywordtype">double</span> down = 1e100;</div>
<div class="line"><a id="l00698" name="l00698"></a><span class="lineno">  698</span>        std::size_t maxUp = ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[0];</div>
<div class="line"><a id="l00699" name="l00699"></a><span class="lineno">  699</span>        std::size_t minDown = ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[0];</div>
<div class="line"><a id="l00700" name="l00700"></a><span class="lineno">  700</span>        <span class="keywordflow">for</span> (std::size_t p = 0; p != pc; p++)</div>
<div class="line"><a id="l00701" name="l00701"></a><span class="lineno">  701</span>        {</div>
<div class="line"><a id="l00702" name="l00702"></a><span class="lineno">  702</span>            std::size_t v = ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[p];</div>
<div class="line"><a id="l00703" name="l00703"></a><span class="lineno">  703</span>            <a class="code hl_define" href="_exception_8h.html#a73abb5049a0168d72a48e72dda41708b">SHARK_ASSERT</a>(v &lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a>);</div>
<div class="line"><a id="l00704" name="l00704"></a><span class="lineno">  704</span>            <span class="keywordtype">double</span> a = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v);</div>
<div class="line"><a id="l00705" name="l00705"></a><span class="lineno">  705</span>            <span class="keywordtype">double</span> g = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(v);</div>
<div class="line"><a id="l00706" name="l00706"></a><span class="lineno">  706</span>            <span class="keywordflow">if</span> (g &gt; up) { </div>
<div class="line"><a id="l00707" name="l00707"></a><span class="lineno">  707</span>                maxUp = v;</div>
<div class="line"><a id="l00708" name="l00708"></a><span class="lineno">  708</span>                up = g;</div>
<div class="line"><a id="l00709" name="l00709"></a><span class="lineno">  709</span>            }</div>
<div class="line"><a id="l00710" name="l00710"></a><span class="lineno">  710</span>            <span class="keywordflow">if</span> (a &gt; 0.0 &amp;&amp; g &lt; down){</div>
<div class="line"><a id="l00711" name="l00711"></a><span class="lineno">  711</span>                minDown = v;</div>
<div class="line"><a id="l00712" name="l00712"></a><span class="lineno">  712</span>                down = g;</div>
<div class="line"><a id="l00713" name="l00713"></a><span class="lineno">  713</span>            }</div>
<div class="line"><a id="l00714" name="l00714"></a><span class="lineno">  714</span>        }</div>
<div class="line"><a id="l00715" name="l00715"></a><span class="lineno">  715</span>        <span class="keywordflow">return</span> std::make_pair(std::make_pair(up,maxUp),std::make_pair(down,minDown));</div>
<div class="line"><a id="l00716" name="l00716"></a><span class="lineno">  716</span>    }</div>
</div>
<div class="line"><a id="l00717" name="l00717"></a><span class="lineno">  717</span>    </div>
<div class="foldopen" id="foldopen00718" data-start="{" data-end="}">
<div class="line"><a id="l00718" name="l00718"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a23aa81fc5a1341bacbbb65f4bba9bd38">  718</a></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a23aa81fc5a1341bacbbb65f4bba9bd38">updateVarsum</a>(std::size_t exampleId, <span class="keywordtype">double</span> mu){</div>
<div class="line"><a id="l00719" name="l00719"></a><span class="lineno">  719</span>        <span class="keywordtype">double</span>&amp; varsum = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[exampleId].varsum;</div>
<div class="line"><a id="l00720" name="l00720"></a><span class="lineno">  720</span>        varsum += mu;</div>
<div class="line"><a id="l00721" name="l00721"></a><span class="lineno">  721</span>        <span class="keywordflow">if</span>(varsum &gt; 1.e-12 &amp;&amp; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>-varsum &gt; 1.e-12*<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>)</div>
<div class="line"><a id="l00722" name="l00722"></a><span class="lineno">  722</span>            <span class="keywordflow">return</span>;</div>
<div class="line"><a id="l00723" name="l00723"></a><span class="lineno">  723</span>        <span class="comment">//recompute for numerical accuracy</span></div>
<div class="line"><a id="l00724" name="l00724"></a><span class="lineno">  724</span>        </div>
<div class="line"><a id="l00725" name="l00725"></a><span class="lineno">  725</span>        varsum = 0;</div>
<div class="line"><a id="l00726" name="l00726"></a><span class="lineno">  726</span>        <span class="keywordflow">for</span>(std::size_t p = 0; p != <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>; ++p){</div>
<div class="line"><a id="l00727" name="l00727"></a><span class="lineno">  727</span>            std::size_t varIndex = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[exampleId].var[p];</div>
<div class="line"><a id="l00728" name="l00728"></a><span class="lineno">  728</span>            varsum += <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>[varIndex];</div>
<div class="line"><a id="l00729" name="l00729"></a><span class="lineno">  729</span>        }</div>
<div class="line"><a id="l00730" name="l00730"></a><span class="lineno">  730</span>        </div>
<div class="line"><a id="l00731" name="l00731"></a><span class="lineno">  731</span>        <span class="keywordflow">if</span>(varsum &lt; 1.e-14)</div>
<div class="line"><a id="l00732" name="l00732"></a><span class="lineno">  732</span>            varsum = 0;</div>
<div class="line"><a id="l00733" name="l00733"></a><span class="lineno">  733</span>        <span class="keywordflow">if</span>(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>-varsum &lt; 1.e-14*<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>)</div>
<div class="line"><a id="l00734" name="l00734"></a><span class="lineno">  734</span>            varsum = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>;</div>
<div class="line"><a id="l00735" name="l00735"></a><span class="lineno">  735</span>    }</div>
</div>
<div class="line"><a id="l00736" name="l00736"></a><span class="lineno">  736</span>    </div>
<div class="foldopen" id="foldopen00737" data-start="{" data-end="}">
<div class="line"><a id="l00737" name="l00737"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a2407864545443c298157fb489c3038f3">  737</a></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a2407864545443c298157fb489c3038f3">gradientUpdate</a>(std::size_t r, <span class="keywordtype">double</span> mu, <a class="code hl_typedef" href="classshark_1_1_qp_mc_simplex_decomp.html#ac2dfe25a10f0c19a059d4a5625a19937">QpFloatType</a>* q)</div>
<div class="line"><a id="l00738" name="l00738"></a><span class="lineno">  738</span>    {</div>
<div class="line"><a id="l00739" name="l00739"></a><span class="lineno">  739</span>        <span class="keywordflow">for</span> ( std::size_t a= 0; a&lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>; a++)</div>
<div class="line"><a id="l00740" name="l00740"></a><span class="lineno">  740</span>        {</div>
<div class="line"><a id="l00741" name="l00741"></a><span class="lineno">  741</span>            <span class="keywordtype">double</span> k = q[a];</div>
<div class="line"><a id="l00742" name="l00742"></a><span class="lineno">  742</span>            <a class="code hl_struct" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html" title="data structure describing one training example">Example</a>&amp; ex = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[a];</div>
<div class="line"><a id="l00743" name="l00743"></a><span class="lineno">  743</span>            <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_qp_sparse_array_1_1_row.html" title="Data structure describing a row of the sparse array.">QpSparseArray&lt;QpFloatType&gt;::Row</a> <span class="keyword">const</span>&amp; row = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a7b64dccd47c7db2a9fa4110b55b52c7c" title="kernel modifiers">m_M</a>.row(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4b3c753187efbb58b433a76face7a52d" title="number of classes in the problem">m_classes</a> * r + ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a289bed9316066dd53203df71f2bfb767" title="label of this example">y</a>);</div>
<div class="line"><a id="l00744" name="l00744"></a><span class="lineno">  744</span>            <a class="code hl_typedef" href="classshark_1_1_qp_mc_simplex_decomp.html#ac2dfe25a10f0c19a059d4a5625a19937">QpFloatType</a> def = row.defaultvalue;</div>
<div class="line"><a id="l00745" name="l00745"></a><span class="lineno">  745</span>            <span class="keywordflow">for</span> (std::size_t b=0; b&lt;row.size; b++){</div>
<div class="line"><a id="l00746" name="l00746"></a><span class="lineno">  746</span>                std::size_t p = row.entry[b].index;</div>
<div class="line"><a id="l00747" name="l00747"></a><span class="lineno">  747</span>                <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ae8e200b285451dd8bfb99672e23984b4" title="list of all m_cardP variables, in order of the p-index">var</a>[p]) -= mu * (row.entry[b].value - def) * k;</div>
<div class="line"><a id="l00748" name="l00748"></a><span class="lineno">  748</span>            }</div>
<div class="line"><a id="l00749" name="l00749"></a><span class="lineno">  749</span>            <span class="keywordflow">if</span> (def != 0.0){</div>
<div class="line"><a id="l00750" name="l00750"></a><span class="lineno">  750</span>                <span class="keywordtype">double</span> upd = mu* def * k;</div>
<div class="line"><a id="l00751" name="l00751"></a><span class="lineno">  751</span>                <span class="keywordflow">for</span> (std::size_t b=0; b&lt;ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aed59b679c1979d9f8ed433f5f56716ab" title="number of active variables">active</a>; b++) </div>
<div class="line"><a id="l00752" name="l00752"></a><span class="lineno">  752</span>                    <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(ex.<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[b]) -= upd;</div>
<div class="line"><a id="l00753" name="l00753"></a><span class="lineno">  753</span>            }</div>
<div class="line"><a id="l00754" name="l00754"></a><span class="lineno">  754</span>        }</div>
<div class="line"><a id="l00755" name="l00755"></a><span class="lineno">  755</span>    }</div>
</div>
<div class="line"><a id="l00756" name="l00756"></a><span class="lineno">  756</span>    <span class="comment"></span></div>
<div class="line"><a id="l00757" name="l00757"></a><span class="lineno">  757</span><span class="comment">    /// shrink a variable</span></div>
<div class="foldopen" id="foldopen00758" data-start="{" data-end="}">
<div class="line"><a id="l00758" name="l00758"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a1d59e69be46dee9ca569fe8f4a4116d3">  758</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a1d59e69be46dee9ca569fe8f4a4116d3" title="shrink a variable">deactivateVariable</a>(std::size_t v)</div>
<div class="line"><a id="l00759" name="l00759"></a><span class="lineno">  759</span>    {</div>
<div class="line"><a id="l00760" name="l00760"></a><span class="lineno">  760</span>        std::size_t ev = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].example;</div>
<div class="line"><a id="l00761" name="l00761"></a><span class="lineno">  761</span>        std::size_t iv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].index;</div>
<div class="line"><a id="l00762" name="l00762"></a><span class="lineno">  762</span>        std::size_t pv = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].p;</div>
<div class="line"><a id="l00763" name="l00763"></a><span class="lineno">  763</span>        <a class="code hl_struct" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html" title="data structure describing one training example">Example</a>* exv = &amp;<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[ev];</div>
<div class="line"><a id="l00764" name="l00764"></a><span class="lineno">  764</span> </div>
<div class="line"><a id="l00765" name="l00765"></a><span class="lineno">  765</span>        std::size_t ih = exv-&gt;<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aed59b679c1979d9f8ed433f5f56716ab" title="number of active variables">active</a> - 1;</div>
<div class="line"><a id="l00766" name="l00766"></a><span class="lineno">  766</span>        std::size_t h = exv-&gt;<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[ih];</div>
<div class="line"><a id="l00767" name="l00767"></a><span class="lineno">  767</span>        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].index = ih;</div>
<div class="line"><a id="l00768" name="l00768"></a><span class="lineno">  768</span>        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[h].index = iv;</div>
<div class="line"><a id="l00769" name="l00769"></a><span class="lineno">  769</span>        std::swap(exv-&gt;<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[iv], exv-&gt;<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[ih]);</div>
<div class="line"><a id="l00770" name="l00770"></a><span class="lineno">  770</span>        iv = ih;</div>
<div class="line"><a id="l00771" name="l00771"></a><span class="lineno">  771</span>        exv-&gt;<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aed59b679c1979d9f8ed433f5f56716ab" title="number of active variables">active</a>--;</div>
<div class="line"><a id="l00772" name="l00772"></a><span class="lineno">  772</span> </div>
<div class="line"><a id="l00773" name="l00773"></a><span class="lineno">  773</span>        std::size_t j = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a> - 1;</div>
<div class="line"><a id="l00774" name="l00774"></a><span class="lineno">  774</span>        std::size_t ej = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[j].example;</div>
<div class="line"><a id="l00775" name="l00775"></a><span class="lineno">  775</span>        std::size_t ij = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[j].index;</div>
<div class="line"><a id="l00776" name="l00776"></a><span class="lineno">  776</span>        std::size_t pj = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[j].p;</div>
<div class="line"><a id="l00777" name="l00777"></a><span class="lineno">  777</span>        <a class="code hl_struct" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html" title="data structure describing one training example">Example</a>* exj = &amp;<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[ej];</div>
<div class="line"><a id="l00778" name="l00778"></a><span class="lineno">  778</span> </div>
<div class="line"><a id="l00779" name="l00779"></a><span class="lineno">  779</span>        <span class="comment">// exchange entries in the lists</span></div>
<div class="line"><a id="l00780" name="l00780"></a><span class="lineno">  780</span>        std::swap(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(v), <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>(j));</div>
<div class="line"><a id="l00781" name="l00781"></a><span class="lineno">  781</span>        std::swap(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(v), <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>(j));</div>
<div class="line"><a id="l00782" name="l00782"></a><span class="lineno">  782</span>        std::swap(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#acae515e014c4002712b8d7204b2e5d36" title="linear part of the objective function">m_linear</a>(v), <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#acae515e014c4002712b8d7204b2e5d36" title="linear part of the objective function">m_linear</a>(j));</div>
<div class="line"><a id="l00783" name="l00783"></a><span class="lineno">  783</span>        std::swap(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v], <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[j]);</div>
<div class="line"><a id="l00784" name="l00784"></a><span class="lineno">  784</span> </div>
<div class="line"><a id="l00785" name="l00785"></a><span class="lineno">  785</span>        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[exv-&gt;<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[iv]].index = ij;</div>
<div class="line"><a id="l00786" name="l00786"></a><span class="lineno">  786</span>        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[exj-&gt;<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[ij]].index = iv;</div>
<div class="line"><a id="l00787" name="l00787"></a><span class="lineno">  787</span>        exv-&gt;<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[iv] = j;</div>
<div class="line"><a id="l00788" name="l00788"></a><span class="lineno">  788</span>        exv-&gt;<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ae8e200b285451dd8bfb99672e23984b4" title="list of all m_cardP variables, in order of the p-index">var</a>[pv] = j;</div>
<div class="line"><a id="l00789" name="l00789"></a><span class="lineno">  789</span>        exj-&gt;<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#a68c607fe9a14561a3d595ca0a5e2d23d" title="list of active variables">avar</a>[ij] = v;</div>
<div class="line"><a id="l00790" name="l00790"></a><span class="lineno">  790</span>        exj-&gt;<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#ae8e200b285451dd8bfb99672e23984b4" title="list of all m_cardP variables, in order of the p-index">var</a>[pj] = v;</div>
<div class="line"><a id="l00791" name="l00791"></a><span class="lineno">  791</span> </div>
<div class="line"><a id="l00792" name="l00792"></a><span class="lineno">  792</span>        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a>--;</div>
<div class="line"><a id="l00793" name="l00793"></a><span class="lineno">  793</span>        </div>
<div class="line"><a id="l00794" name="l00794"></a><span class="lineno">  794</span>        <span class="comment">//finally check if the example is needed anymore</span></div>
<div class="line"><a id="l00795" name="l00795"></a><span class="lineno">  795</span>        <span class="keywordflow">if</span>(exv-&gt;<a class="code hl_variable" href="structshark_1_1_qp_mc_simplex_decomp_1_1_example.html#aed59b679c1979d9f8ed433f5f56716ab" title="number of active variables">active</a> == 0)</div>
<div class="line"><a id="l00796" name="l00796"></a><span class="lineno">  796</span>            <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#afd8b5d8d95c2235fe44423d9833761bd" title="shrink an example">deactivateExample</a>(ev);</div>
<div class="line"><a id="l00797" name="l00797"></a><span class="lineno">  797</span>    }</div>
</div>
<div class="line"><a id="l00798" name="l00798"></a><span class="lineno">  798</span><span class="comment"></span> </div>
<div class="line"><a id="l00799" name="l00799"></a><span class="lineno">  799</span><span class="comment">    /// shrink an example</span></div>
<div class="foldopen" id="foldopen00800" data-start="{" data-end="}">
<div class="line"><a id="l00800" name="l00800"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#afd8b5d8d95c2235fe44423d9833761bd">  800</a></span><span class="comment"></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#afd8b5d8d95c2235fe44423d9833761bd" title="shrink an example">deactivateExample</a>(std::size_t e)</div>
<div class="line"><a id="l00801" name="l00801"></a><span class="lineno">  801</span>    {</div>
<div class="line"><a id="l00802" name="l00802"></a><span class="lineno">  802</span>        <a class="code hl_define" href="_exception_8h.html#a73abb5049a0168d72a48e72dda41708b">SHARK_ASSERT</a>(e &lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>);</div>
<div class="line"><a id="l00803" name="l00803"></a><span class="lineno">  803</span>        std::size_t j = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a> - 1;</div>
<div class="line"><a id="l00804" name="l00804"></a><span class="lineno">  804</span>        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>--;</div>
<div class="line"><a id="l00805" name="l00805"></a><span class="lineno">  805</span>        <span class="keywordflow">if</span>(e == j) <span class="keywordflow">return</span>;</div>
<div class="line"><a id="l00806" name="l00806"></a><span class="lineno">  806</span> </div>
<div class="line"><a id="l00807" name="l00807"></a><span class="lineno">  807</span>        std::swap(<a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[e], <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[j]);</div>
<div class="line"><a id="l00808" name="l00808"></a><span class="lineno">  808</span> </div>
<div class="line"><a id="l00809" name="l00809"></a><span class="lineno">  809</span>        std::size_t* pe = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[e].var;</div>
<div class="line"><a id="l00810" name="l00810"></a><span class="lineno">  810</span>        std::size_t* pj = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[j].var;</div>
<div class="line"><a id="l00811" name="l00811"></a><span class="lineno">  811</span>        <span class="keywordflow">for</span> (std::size_t v = 0; v &lt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>; v++)</div>
<div class="line"><a id="l00812" name="l00812"></a><span class="lineno">  812</span>        {</div>
<div class="line"><a id="l00813" name="l00813"></a><span class="lineno">  813</span>            <a class="code hl_define" href="_exception_8h.html#a73abb5049a0168d72a48e72dda41708b">SHARK_ASSERT</a>(pj[v] &gt;= <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a>);</div>
<div class="line"><a id="l00814" name="l00814"></a><span class="lineno">  814</span>            <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[pe[v]].example = e;</div>
<div class="line"><a id="l00815" name="l00815"></a><span class="lineno">  815</span>            <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[pj[v]].example = j;</div>
<div class="line"><a id="l00816" name="l00816"></a><span class="lineno">  816</span>        }</div>
<div class="line"><a id="l00817" name="l00817"></a><span class="lineno">  817</span>        <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ac8b9a895906060a9d50e13b0523d4255" title="kernel matrix (precomputed matrix or matrix cache)">m_kernelMatrix</a>.flipColumnsAndRows(e, j);</div>
<div class="line"><a id="l00818" name="l00818"></a><span class="lineno">  818</span>    }</div>
</div>
<div class="line"><a id="l00819" name="l00819"></a><span class="lineno">  819</span>    <span class="comment"></span></div>
<div class="line"><a id="l00820" name="l00820"></a><span class="lineno">  820</span><span class="comment">    /// \brief Returns the original index of the example of a variable in the dataset before optimization.</span></div>
<div class="line"><a id="l00821" name="l00821"></a><span class="lineno">  821</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00822" name="l00822"></a><span class="lineno">  822</span><span class="comment">    /// Shrinking is an internal detail so the communication with the outside world uses the original indizes.</span></div>
<div class="foldopen" id="foldopen00823" data-start="{" data-end="}">
<div class="line"><a id="l00823" name="l00823"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a35458b4d12a371cf221c1643e7295072">  823</a></span><span class="comment"></span>    std::size_t <a class="code hl_function" href="classshark_1_1_qp_mc_simplex_decomp.html#a35458b4d12a371cf221c1643e7295072" title="Returns the original index of the example of a variable in the dataset before optimization.">originalIndex</a>(std::size_t v)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00824" name="l00824"></a><span class="lineno">  824</span>        std::size_t i = <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>[v].example;</div>
<div class="line"><a id="l00825" name="l00825"></a><span class="lineno">  825</span>        <span class="keywordflow">return</span> <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>[i].index;<span class="comment">//i before shrinking</span></div>
<div class="line"><a id="l00826" name="l00826"></a><span class="lineno">  826</span>    }</div>
</div>
<div class="line"><a id="l00827" name="l00827"></a><span class="lineno">  827</span><span class="comment"></span> </div>
<div class="line"><a id="l00828" name="l00828"></a><span class="lineno">  828</span><span class="comment">    /// kernel matrix (precomputed matrix or matrix cache)</span></div>
<div class="line"><a id="l00829" name="l00829"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#ac8b9a895906060a9d50e13b0523d4255">  829</a></span><span class="comment"></span>    Matrix&amp; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ac8b9a895906060a9d50e13b0523d4255" title="kernel matrix (precomputed matrix or matrix cache)">m_kernelMatrix</a>;</div>
<div class="line"><a id="l00830" name="l00830"></a><span class="lineno">  830</span><span class="comment"></span> </div>
<div class="line"><a id="l00831" name="l00831"></a><span class="lineno">  831</span><span class="comment">    /// kernel modifiers</span></div>
<div class="line"><a id="l00832" name="l00832"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a7b64dccd47c7db2a9fa4110b55b52c7c">  832</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_qp_sparse_array.html" title="specialized container class for multi-class SVM problems">QpSparseArray&lt;QpFloatType&gt;</a> <span class="keyword">const</span>&amp; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a7b64dccd47c7db2a9fa4110b55b52c7c" title="kernel modifiers">m_M</a>;          <span class="comment">// M(|P|*y_i+p, y_j, q)</span></div>
<div class="line"><a id="l00833" name="l00833"></a><span class="lineno">  833</span><span class="comment"></span> </div>
<div class="line"><a id="l00834" name="l00834"></a><span class="lineno">  834</span><span class="comment">    /// complexity constant; upper bound on all variabless</span></div>
<div class="line"><a id="l00835" name="l00835"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e">  835</a></span><span class="comment"></span>    <span class="keywordtype">double</span> <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9a6ceeb1c95124d14fd75a061282063e" title="complexity constant; upper bound on all variabless">m_C</a>;</div>
<div class="line"><a id="l00836" name="l00836"></a><span class="lineno">  836</span>    <span class="comment"></span></div>
<div class="line"><a id="l00837" name="l00837"></a><span class="lineno">  837</span><span class="comment">    /// number of classes in the problem</span></div>
<div class="line"><a id="l00838" name="l00838"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a4b3c753187efbb58b433a76face7a52d">  838</a></span><span class="comment"></span>    std::size_t <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4b3c753187efbb58b433a76face7a52d" title="number of classes in the problem">m_classes</a>;</div>
<div class="line"><a id="l00839" name="l00839"></a><span class="lineno">  839</span>    <span class="comment"></span></div>
<div class="line"><a id="l00840" name="l00840"></a><span class="lineno">  840</span><span class="comment">    /// number of dual variables per example</span></div>
<div class="line"><a id="l00841" name="l00841"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698">  841</a></span><span class="comment"></span>    std::size_t <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a4998fe91e32ad7b0248b7ae9bf049698" title="number of dual variables per example">m_cardP</a>;</div>
<div class="line"><a id="l00842" name="l00842"></a><span class="lineno">  842</span>    <span class="comment"></span></div>
<div class="line"><a id="l00843" name="l00843"></a><span class="lineno">  843</span><span class="comment">    /// number of examples in the problem (size of the kernel matrix)</span></div>
<div class="line"><a id="l00844" name="l00844"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287">  844</a></span><span class="comment"></span>    std::size_t <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a6bb02dd76df204682c6c914b9c6d8287" title="number of examples in the problem (size of the kernel matrix)">m_numExamples</a>;</div>
<div class="line"><a id="l00845" name="l00845"></a><span class="lineno">  845</span><span class="comment"></span> </div>
<div class="line"><a id="l00846" name="l00846"></a><span class="lineno">  846</span><span class="comment">    /// number of variables in the problem = m_numExamples * m_cardP</span></div>
<div class="line"><a id="l00847" name="l00847"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c">  847</a></span><span class="comment"></span>    std::size_t <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a837aabb43bc054e78dc73e831e6ac95c" title="number of variables in the problem = m_numExamples * m_cardP">m_numVariables</a>;</div>
<div class="line"><a id="l00848" name="l00848"></a><span class="lineno">  848</span>    <span class="comment"></span></div>
<div class="line"><a id="l00849" name="l00849"></a><span class="lineno">  849</span><span class="comment">    /// linear part of the objective function</span></div>
<div class="line"><a id="l00850" name="l00850"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#acae515e014c4002712b8d7204b2e5d36">  850</a></span><span class="comment"></span>    RealVector <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#acae515e014c4002712b8d7204b2e5d36" title="linear part of the objective function">m_linear</a>;</div>
<div class="line"><a id="l00851" name="l00851"></a><span class="lineno">  851</span>    <span class="comment"></span></div>
<div class="line"><a id="l00852" name="l00852"></a><span class="lineno">  852</span><span class="comment">    /// solution candidate</span></div>
<div class="line"><a id="l00853" name="l00853"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632">  853</a></span><span class="comment"></span>    RealVector <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a273c3111e4f92b69208b8d6956d92632" title="solution candidate">m_alpha</a>;</div>
<div class="line"><a id="l00854" name="l00854"></a><span class="lineno">  854</span>    <span class="comment"></span></div>
<div class="line"><a id="l00855" name="l00855"></a><span class="lineno">  855</span><span class="comment">    /// gradient of the objective function</span></div>
<div class="line"><a id="l00856" name="l00856"></a><span class="lineno">  856</span><span class="comment">    /// The m_gradient array is of fixed size and not subject to shrinking.</span></div>
<div class="line"><a id="l00857" name="l00857"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">  857</a></span><span class="comment"></span>    RealVector <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae10be0310484cc2dd7b23e17a9eb2a7d">m_gradient</a>;</div>
<div class="line"><a id="l00858" name="l00858"></a><span class="lineno">  858</span><span class="comment"></span> </div>
<div class="line"><a id="l00859" name="l00859"></a><span class="lineno">  859</span><span class="comment">    /// information about each training example</span></div>
<div class="line"><a id="l00860" name="l00860"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8">  860</a></span><span class="comment"></span>    std::vector&lt;Example&gt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a5a5b7d832f3d8ac9cf0cc485e6339ac8" title="information about each training example">m_examples</a>;</div>
<div class="line"><a id="l00861" name="l00861"></a><span class="lineno">  861</span><span class="comment"></span> </div>
<div class="line"><a id="l00862" name="l00862"></a><span class="lineno">  862</span><span class="comment">    /// information about each variable of the problem</span></div>
<div class="line"><a id="l00863" name="l00863"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d">  863</a></span><span class="comment"></span>    std::vector&lt;Variable&gt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af6d2c8d896fddf2d93b6c3941301ca3d" title="information about each variable of the problem">m_variables</a>;</div>
<div class="line"><a id="l00864" name="l00864"></a><span class="lineno">  864</span><span class="comment"></span> </div>
<div class="line"><a id="l00865" name="l00865"></a><span class="lineno">  865</span><span class="comment">    /// space for the example[i].var pointers</span></div>
<div class="line"><a id="l00866" name="l00866"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a9b901d9fb12638fcbf12704c0bf41bcd">  866</a></span><span class="comment"></span>    std::vector&lt;std::size_t&gt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a9b901d9fb12638fcbf12704c0bf41bcd" title="space for the example[i].var pointers">m_storage1</a>;</div>
<div class="line"><a id="l00867" name="l00867"></a><span class="lineno">  867</span><span class="comment"></span> </div>
<div class="line"><a id="l00868" name="l00868"></a><span class="lineno">  868</span><span class="comment">    /// space for the example[i].avar pointers</span></div>
<div class="line"><a id="l00869" name="l00869"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#a3e94df73fba2f12fcbdc923c062ff752">  869</a></span><span class="comment"></span>    std::vector&lt;std::size_t&gt; <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#a3e94df73fba2f12fcbdc923c062ff752" title="space for the example[i].avar pointers">m_storage2</a>;</div>
<div class="line"><a id="l00870" name="l00870"></a><span class="lineno">  870</span><span class="comment"></span> </div>
<div class="line"><a id="l00871" name="l00871"></a><span class="lineno">  871</span><span class="comment">    /// number of currently active examples</span></div>
<div class="line"><a id="l00872" name="l00872"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838">  872</a></span><span class="comment"></span>    std::size_t <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ad7997f63459adc594c8d1cd649438838" title="number of currently active examples">m_activeEx</a>;</div>
<div class="line"><a id="l00873" name="l00873"></a><span class="lineno">  873</span><span class="comment"></span> </div>
<div class="line"><a id="l00874" name="l00874"></a><span class="lineno">  874</span><span class="comment">    /// number of currently active variables</span></div>
<div class="line"><a id="l00875" name="l00875"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f">  875</a></span><span class="comment"></span>    std::size_t <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#aac002eeaa49e5ff3b667f9934d92392f" title="number of currently active variables">m_activeVar</a>;</div>
<div class="line"><a id="l00876" name="l00876"></a><span class="lineno">  876</span><span class="comment"></span> </div>
<div class="line"><a id="l00877" name="l00877"></a><span class="lineno">  877</span><span class="comment">    /// should the m_problem use the shrinking heuristics?</span></div>
<div class="line"><a id="l00878" name="l00878"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#af69f443110c3a0e0c6d34ec331c71a8a">  878</a></span><span class="comment"></span>    <span class="keywordtype">bool</span> <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#af69f443110c3a0e0c6d34ec331c71a8a" title="should the m_problem use the shrinking heuristics?">m_useShrinking</a>;</div>
<div class="line"><a id="l00879" name="l00879"></a><span class="lineno">  879</span>    <span class="comment"></span></div>
<div class="line"><a id="l00880" name="l00880"></a><span class="lineno">  880</span><span class="comment">    /// true if the problem has already been unshrinked</span></div>
<div class="line"><a id="l00881" name="l00881"></a><span class="lineno"><a class="line" href="classshark_1_1_qp_mc_simplex_decomp.html#ae4356261aaf70b6569308fa13f01a56a">  881</a></span><span class="comment"></span>    <span class="keywordtype">bool</span> <a class="code hl_variable" href="classshark_1_1_qp_mc_simplex_decomp.html#ae4356261aaf70b6569308fa13f01a56a" title="true if the problem has already been unshrinked">bUnshrinked</a>;</div>
<div class="line"><a id="l00882" name="l00882"></a><span class="lineno">  882</span>};</div>
</div>
<div class="line"><a id="l00883" name="l00883"></a><span class="lineno">  883</span> </div>
<div class="line"><a id="l00884" name="l00884"></a><span class="lineno">  884</span> </div>
<div class="line"><a id="l00885" name="l00885"></a><span class="lineno">  885</span><span class="keyword">template</span>&lt;<span class="keyword">class</span> Matrix&gt;</div>
<div class="foldopen" id="foldopen00886" data-start="{" data-end="};">
<div class="line"><a id="l00886" name="l00886"></a><span class="lineno"><a class="line" href="classshark_1_1_bias_solver_simplex.html">  886</a></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_bias_solver_simplex.html">BiasSolverSimplex</a>{</div>
<div class="line"><a id="l00887" name="l00887"></a><span class="lineno">  887</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00888" name="l00888"></a><span class="lineno"><a class="line" href="classshark_1_1_bias_solver_simplex.html#a0e378330105c3585628efb53be8fa610">  888</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> Matrix::QpFloatType <a class="code hl_typedef" href="classshark_1_1_bias_solver_simplex.html#a0e378330105c3585628efb53be8fa610">QpFloatType</a>;</div>
<div class="line"><a id="l00889" name="l00889"></a><span class="lineno"><a class="line" href="classshark_1_1_bias_solver_simplex.html#a63c458c8a8636282d49b4f1cba6cbd00">  889</a></span>    <a class="code hl_function" href="classshark_1_1_bias_solver_simplex.html#a63c458c8a8636282d49b4f1cba6cbd00">BiasSolverSimplex</a>(<a class="code hl_class" href="classshark_1_1_qp_mc_simplex_decomp.html">QpMcSimplexDecomp&lt;Matrix&gt;</a>* problem) : m_problem(problem){}</div>
<div class="line"><a id="l00890" name="l00890"></a><span class="lineno">  890</span>        </div>
<div class="foldopen" id="foldopen00891" data-start="{" data-end="}">
<div class="line"><a id="l00891" name="l00891"></a><span class="lineno"><a class="line" href="classshark_1_1_bias_solver_simplex.html#a60479f4edcd9038d612da5c34d4e6022">  891</a></span>    <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_bias_solver_simplex.html#a60479f4edcd9038d612da5c34d4e6022">solve</a>(</div>
<div class="line"><a id="l00892" name="l00892"></a><span class="lineno">  892</span>        RealVector&amp; bias,</div>
<div class="line"><a id="l00893" name="l00893"></a><span class="lineno">  893</span>        <a class="code hl_struct" href="structshark_1_1_qp_stopping_condition.html" title="stopping conditions for quadratic programming">QpStoppingCondition</a>&amp; stop,</div>
<div class="line"><a id="l00894" name="l00894"></a><span class="lineno">  894</span>        <a class="code hl_class" href="classshark_1_1_qp_sparse_array.html" title="specialized container class for multi-class SVM problems">QpSparseArray&lt;QpFloatType&gt;</a> <span class="keyword">const</span>&amp; nu,</div>
<div class="line"><a id="l00895" name="l00895"></a><span class="lineno">  895</span>        <span class="keywordtype">bool</span> sumToZero,</div>
<div class="line"><a id="l00896" name="l00896"></a><span class="lineno">  896</span>        <a class="code hl_struct" href="structshark_1_1_qp_solution_properties.html" title="properties of the solution of a quadratic program">QpSolutionProperties</a>* prop = NULL</div>
<div class="line"><a id="l00897" name="l00897"></a><span class="lineno">  897</span>    ){</div>
<div class="line"><a id="l00898" name="l00898"></a><span class="lineno">  898</span>        std::size_t classes = bias.size();</div>
<div class="line"><a id="l00899" name="l00899"></a><span class="lineno">  899</span>        std::size_t numExamples = m_problem-&gt;getNumExamples();</div>
<div class="line"><a id="l00900" name="l00900"></a><span class="lineno">  900</span>        std::size_t cardP = m_problem-&gt;cardP();</div>
<div class="line"><a id="l00901" name="l00901"></a><span class="lineno">  901</span>        RealVector stepsize(classes, 0.01);</div>
<div class="line"><a id="l00902" name="l00902"></a><span class="lineno">  902</span>        RealVector prev(classes,0);</div>
<div class="line"><a id="l00903" name="l00903"></a><span class="lineno">  903</span>        RealVector step(classes);</div>
<div class="line"><a id="l00904" name="l00904"></a><span class="lineno">  904</span>        </div>
<div class="line"><a id="l00905" name="l00905"></a><span class="lineno">  905</span>        <span class="keywordtype">double</span> start_time = <a class="code hl_function" href="classshark_1_1_timer.html#a4a3f88c6b69f2ed99176ee4c28057c6b" title="Returns the current time in a microsecond resolution. Att: may in rare cases give decreasing values.">Timer::now</a>();</div>
<div class="line"><a id="l00906" name="l00906"></a><span class="lineno">  906</span>        <span class="keywordtype">unsigned</span> <span class="keywordtype">long</span> <span class="keywordtype">long</span> iterations = 0;</div>
<div class="line"><a id="l00907" name="l00907"></a><span class="lineno">  907</span>        </div>
<div class="line"><a id="l00908" name="l00908"></a><span class="lineno">  908</span>        <span class="keywordflow">do</span>{</div>
<div class="line"><a id="l00909" name="l00909"></a><span class="lineno">  909</span>            <a class="code hl_struct" href="structshark_1_1_qp_solution_properties.html" title="properties of the solution of a quadratic program">QpSolutionProperties</a> propInner;</div>
<div class="line"><a id="l00910" name="l00910"></a><span class="lineno">  910</span>            <a class="code hl_class" href="classshark_1_1_qp_solver.html" title="Quadratic program solver.">QpSolver&lt;QpMcSimplexDecomp&lt;Matrix&gt;</a> &gt; solver(*m_problem);</div>
<div class="line"><a id="l00911" name="l00911"></a><span class="lineno">  911</span>            solver.<a class="code hl_function" href="classshark_1_1_qp_solver.html#aef891551dc0bc92ab4571cb7d479706f" title="Solve the quadratic program.">solve</a>(stop, &amp;propInner);</div>
<div class="line"><a id="l00912" name="l00912"></a><span class="lineno">  912</span>            iterations += propInner.<a class="code hl_variable" href="structshark_1_1_qp_solution_properties.html#aa1b7fb15931dfebb70364b0bf949fa15" title="number of decomposition iterations">iterations</a>;</div>
<div class="line"><a id="l00913" name="l00913"></a><span class="lineno">  913</span> </div>
<div class="line"><a id="l00914" name="l00914"></a><span class="lineno">  914</span>            <span class="comment">// Rprop loop to update the bias</span></div>
<div class="line"><a id="l00915" name="l00915"></a><span class="lineno">  915</span>            <span class="keywordflow">while</span> (<span class="keyword">true</span>)</div>
<div class="line"><a id="l00916" name="l00916"></a><span class="lineno">  916</span>            {</div>
<div class="line"><a id="l00917" name="l00917"></a><span class="lineno">  917</span>                RealMatrix dualGradient = m_problem-&gt;solutionGradient();</div>
<div class="line"><a id="l00918" name="l00918"></a><span class="lineno">  918</span>                <span class="comment">// compute the primal m_gradient w.r.t. bias</span></div>
<div class="line"><a id="l00919" name="l00919"></a><span class="lineno">  919</span>                RealVector grad(classes,0);</div>
<div class="line"><a id="l00920" name="l00920"></a><span class="lineno">  920</span>                </div>
<div class="line"><a id="l00921" name="l00921"></a><span class="lineno">  921</span>                <span class="keywordflow">for</span> (std::size_t i=0; i&lt;numExamples; i++){</div>
<div class="line"><a id="l00922" name="l00922"></a><span class="lineno">  922</span>                    std::size_t largestP = cardP;</div>
<div class="line"><a id="l00923" name="l00923"></a><span class="lineno">  923</span>                    <span class="keywordtype">double</span> largest_value = 0.0;</div>
<div class="line"><a id="l00924" name="l00924"></a><span class="lineno">  924</span>                    <span class="keywordflow">for</span> (std::size_t p=0; p&lt;cardP; p++)</div>
<div class="line"><a id="l00925" name="l00925"></a><span class="lineno">  925</span>                    {</div>
<div class="line"><a id="l00926" name="l00926"></a><span class="lineno">  926</span>                        <span class="keywordflow">if</span> (dualGradient(i,p) &gt; largest_value)</div>
<div class="line"><a id="l00927" name="l00927"></a><span class="lineno">  927</span>                        {</div>
<div class="line"><a id="l00928" name="l00928"></a><span class="lineno">  928</span>                            largest_value = dualGradient(i,p);</div>
<div class="line"><a id="l00929" name="l00929"></a><span class="lineno">  929</span>                            largestP = p;</div>
<div class="line"><a id="l00930" name="l00930"></a><span class="lineno">  930</span>                        }</div>
<div class="line"><a id="l00931" name="l00931"></a><span class="lineno">  931</span>                    }</div>
<div class="line"><a id="l00932" name="l00932"></a><span class="lineno">  932</span>                    <span class="keywordflow">if</span> (largestP &lt; cardP)</div>
<div class="line"><a id="l00933" name="l00933"></a><span class="lineno">  933</span>                    {</div>
<div class="line"><a id="l00934" name="l00934"></a><span class="lineno">  934</span>                        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> y = m_problem-&gt;label(i);</div>
<div class="line"><a id="l00935" name="l00935"></a><span class="lineno">  935</span>                        <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_qp_sparse_array_1_1_row.html" title="Data structure describing a row of the sparse array.">QpSparseArray&lt;QpFloatType&gt;::Row</a> <span class="keyword">const</span>&amp; row = nu.<a class="code hl_function" href="classshark_1_1_qp_sparse_array.html#a48374ef20f984fd3d290600fc5af63f8" title="obtain a row of the matrix">row</a>(y * cardP + largestP);</div>
<div class="line"><a id="l00936" name="l00936"></a><span class="lineno">  936</span>                        <span class="keywordflow">for</span> (std::size_t b=0; b != row.size; b++) </div>
<div class="line"><a id="l00937" name="l00937"></a><span class="lineno">  937</span>                            grad(row.entry[b].index) -= row.entry[b].value;</div>
<div class="line"><a id="l00938" name="l00938"></a><span class="lineno">  938</span>                    }</div>
<div class="line"><a id="l00939" name="l00939"></a><span class="lineno">  939</span>                }</div>
<div class="line"><a id="l00940" name="l00940"></a><span class="lineno">  940</span> </div>
<div class="line"><a id="l00941" name="l00941"></a><span class="lineno">  941</span>                <span class="keywordflow">if</span> (sumToZero)</div>
<div class="line"><a id="l00942" name="l00942"></a><span class="lineno">  942</span>                {</div>
<div class="line"><a id="l00943" name="l00943"></a><span class="lineno">  943</span>                    <span class="comment">// project the m_gradient</span></div>
<div class="line"><a id="l00944" name="l00944"></a><span class="lineno">  944</span>                    grad -= sum(grad) / classes;</div>
<div class="line"><a id="l00945" name="l00945"></a><span class="lineno">  945</span>                }</div>
<div class="line"><a id="l00946" name="l00946"></a><span class="lineno">  946</span> </div>
<div class="line"><a id="l00947" name="l00947"></a><span class="lineno">  947</span>                <span class="comment">// Rprop</span></div>
<div class="line"><a id="l00948" name="l00948"></a><span class="lineno">  948</span>                <span class="keywordflow">for</span> (std::size_t c=0; c&lt;classes; c++)</div>
<div class="line"><a id="l00949" name="l00949"></a><span class="lineno">  949</span>                {</div>
<div class="line"><a id="l00950" name="l00950"></a><span class="lineno">  950</span>                    <span class="keywordtype">double</span> g = grad(c);</div>
<div class="line"><a id="l00951" name="l00951"></a><span class="lineno">  951</span>                    <span class="keywordflow">if</span> (g &gt; 0.0) </div>
<div class="line"><a id="l00952" name="l00952"></a><span class="lineno">  952</span>                        step(c) = -stepsize(c);</div>
<div class="line"><a id="l00953" name="l00953"></a><span class="lineno">  953</span>                    <span class="keywordflow">else</span> <span class="keywordflow">if</span> (g &lt; 0.0) </div>
<div class="line"><a id="l00954" name="l00954"></a><span class="lineno">  954</span>                        step(c) = stepsize(c);</div>
<div class="line"><a id="l00955" name="l00955"></a><span class="lineno">  955</span> </div>
<div class="line"><a id="l00956" name="l00956"></a><span class="lineno">  956</span>                    <span class="keywordtype">double</span> gg = prev(c) * grad(c);</div>
<div class="line"><a id="l00957" name="l00957"></a><span class="lineno">  957</span>                    <span class="keywordflow">if</span> (gg &gt; 0.0) </div>
<div class="line"><a id="l00958" name="l00958"></a><span class="lineno">  958</span>                        stepsize(c) *= 1.2;</div>
<div class="line"><a id="l00959" name="l00959"></a><span class="lineno">  959</span>                    <span class="keywordflow">else</span> </div>
<div class="line"><a id="l00960" name="l00960"></a><span class="lineno">  960</span>                        stepsize(c) *= 0.5;</div>
<div class="line"><a id="l00961" name="l00961"></a><span class="lineno">  961</span>                }</div>
<div class="line"><a id="l00962" name="l00962"></a><span class="lineno">  962</span>                prev = grad;</div>
<div class="line"><a id="l00963" name="l00963"></a><span class="lineno">  963</span> </div>
<div class="line"><a id="l00964" name="l00964"></a><span class="lineno">  964</span>                <span class="keywordflow">if</span> (sumToZero)</div>
<div class="line"><a id="l00965" name="l00965"></a><span class="lineno">  965</span>                {</div>
<div class="line"><a id="l00966" name="l00966"></a><span class="lineno">  966</span>                    <span class="comment">// project the step</span></div>
<div class="line"><a id="l00967" name="l00967"></a><span class="lineno">  967</span>                    step -= sum(step) / classes;</div>
<div class="line"><a id="l00968" name="l00968"></a><span class="lineno">  968</span>                }</div>
<div class="line"><a id="l00969" name="l00969"></a><span class="lineno">  969</span> </div>
<div class="line"><a id="l00970" name="l00970"></a><span class="lineno">  970</span>                <span class="comment">// update the solution and the dual m_gradient</span></div>
<div class="line"><a id="l00971" name="l00971"></a><span class="lineno">  971</span>                bias += step;</div>
<div class="line"><a id="l00972" name="l00972"></a><span class="lineno">  972</span>                performBiasUpdate(step,nu);</div>
<div class="line"><a id="l00973" name="l00973"></a><span class="lineno">  973</span>                </div>
<div class="line"><a id="l00974" name="l00974"></a><span class="lineno">  974</span>                <span class="keywordflow">if</span> (max(stepsize) &lt; 0.01 * stop.<a class="code hl_variable" href="structshark_1_1_qp_stopping_condition.html#addc2ea7f6d15eb25187586e329f33ace" title="minimum accuracy to be achieved, usually KKT violation">minAccuracy</a>) <span class="keywordflow">break</span>;</div>
<div class="line"><a id="l00975" name="l00975"></a><span class="lineno">  975</span>            }</div>
<div class="line"><a id="l00976" name="l00976"></a><span class="lineno">  976</span>        }<span class="keywordflow">while</span>(m_problem-&gt;checkKKT()&gt; stop.<a class="code hl_variable" href="structshark_1_1_qp_stopping_condition.html#addc2ea7f6d15eb25187586e329f33ace" title="minimum accuracy to be achieved, usually KKT violation">minAccuracy</a>);</div>
<div class="line"><a id="l00977" name="l00977"></a><span class="lineno">  977</span>        </div>
<div class="line"><a id="l00978" name="l00978"></a><span class="lineno">  978</span>        <span class="keywordflow">if</span> (prop != NULL)</div>
<div class="line"><a id="l00979" name="l00979"></a><span class="lineno">  979</span>        {</div>
<div class="line"><a id="l00980" name="l00980"></a><span class="lineno">  980</span>            <span class="keywordtype">double</span> finish_time = <a class="code hl_function" href="classshark_1_1_timer.html#a4a3f88c6b69f2ed99176ee4c28057c6b" title="Returns the current time in a microsecond resolution. Att: may in rare cases give decreasing values.">Timer::now</a>();</div>
<div class="line"><a id="l00981" name="l00981"></a><span class="lineno">  981</span>            </div>
<div class="line"><a id="l00982" name="l00982"></a><span class="lineno">  982</span>            prop-&gt;accuracy = m_problem-&gt;checkKKT();</div>
<div class="line"><a id="l00983" name="l00983"></a><span class="lineno">  983</span>            prop-&gt;value = m_problem-&gt;functionValue();</div>
<div class="line"><a id="l00984" name="l00984"></a><span class="lineno">  984</span>            prop-&gt;iterations = iterations;</div>
<div class="line"><a id="l00985" name="l00985"></a><span class="lineno">  985</span>            prop-&gt;seconds = finish_time - start_time;</div>
<div class="line"><a id="l00986" name="l00986"></a><span class="lineno">  986</span>        }</div>
<div class="line"><a id="l00987" name="l00987"></a><span class="lineno">  987</span>    }</div>
</div>
<div class="line"><a id="l00988" name="l00988"></a><span class="lineno">  988</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00989" name="l00989"></a><span class="lineno">  989</span>    <span class="keywordtype">void</span> performBiasUpdate(</div>
<div class="line"><a id="l00990" name="l00990"></a><span class="lineno">  990</span>        RealVector <span class="keyword">const</span>&amp; step, <a class="code hl_class" href="classshark_1_1_qp_sparse_array.html" title="specialized container class for multi-class SVM problems">QpSparseArray&lt;QpFloatType&gt;</a> <span class="keyword">const</span>&amp; nu</div>
<div class="line"><a id="l00991" name="l00991"></a><span class="lineno">  991</span>    ){</div>
<div class="line"><a id="l00992" name="l00992"></a><span class="lineno">  992</span>        std::size_t numExamples = m_problem-&gt;getNumExamples();</div>
<div class="line"><a id="l00993" name="l00993"></a><span class="lineno">  993</span>        std::size_t cardP = m_problem-&gt;cardP();</div>
<div class="line"><a id="l00994" name="l00994"></a><span class="lineno">  994</span>        RealMatrix deltaLinear(numExamples,cardP,0.0);</div>
<div class="line"><a id="l00995" name="l00995"></a><span class="lineno">  995</span>        <span class="keywordflow">for</span> (std::size_t i=0; i&lt;numExamples; i++){</div>
<div class="line"><a id="l00996" name="l00996"></a><span class="lineno">  996</span>            <span class="keywordflow">for</span> (std::size_t p=0; p&lt;cardP; p++){</div>
<div class="line"><a id="l00997" name="l00997"></a><span class="lineno">  997</span>                <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> y = m_problem-&gt;label(i);</div>
<div class="line"><a id="l00998" name="l00998"></a><span class="lineno">  998</span>                <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_qp_sparse_array_1_1_row.html" title="Data structure describing a row of the sparse array.">QpSparseArray&lt;QpFloatType&gt;::Row</a> <span class="keyword">const</span>&amp; row = nu.<a class="code hl_function" href="classshark_1_1_qp_sparse_array.html#a48374ef20f984fd3d290600fc5af63f8" title="obtain a row of the matrix">row</a>(y * cardP +p);</div>
<div class="line"><a id="l00999" name="l00999"></a><span class="lineno">  999</span>                <span class="keywordflow">for</span> (std::size_t b=0; b&lt;row.size; b++)</div>
<div class="line"><a id="l01000" name="l01000"></a><span class="lineno"> 1000</span>                {</div>
<div class="line"><a id="l01001" name="l01001"></a><span class="lineno"> 1001</span>                    deltaLinear(i,p) -= row.entry[b].value * step(row.entry[b].index);</div>
<div class="line"><a id="l01002" name="l01002"></a><span class="lineno"> 1002</span>                }</div>
<div class="line"><a id="l01003" name="l01003"></a><span class="lineno"> 1003</span>            }</div>
<div class="line"><a id="l01004" name="l01004"></a><span class="lineno"> 1004</span>        }</div>
<div class="line"><a id="l01005" name="l01005"></a><span class="lineno"> 1005</span>        m_problem-&gt;addDeltaLinear(deltaLinear);</div>
<div class="line"><a id="l01006" name="l01006"></a><span class="lineno"> 1006</span>        </div>
<div class="line"><a id="l01007" name="l01007"></a><span class="lineno"> 1007</span>    }</div>
<div class="line"><a id="l01008" name="l01008"></a><span class="lineno"> 1008</span>    QpMcSimplexDecomp&lt;Matrix&gt;* m_problem;</div>
<div class="line"><a id="l01009" name="l01009"></a><span class="lineno"> 1009</span>};</div>
</div>
<div class="line"><a id="l01010" name="l01010"></a><span class="lineno"> 1010</span> </div>
<div class="line"><a id="l01011" name="l01011"></a><span class="lineno"> 1011</span> </div>
<div class="line"><a id="l01012" name="l01012"></a><span class="lineno"> 1012</span>}</div>
<div class="line"><a id="l01013" name="l01013"></a><span class="lineno"> 1013</span><span class="preprocessor">#endif</span></div>
</div><!-- fragment --></div><!-- contents -->
</div>
</body>
</html>
